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1,004 results on '"A. Toyama"'

1. Novel Measurement of the Neutron Magnetic Form Factor from A=3 Mirror Nuclei

Author: Santiesteban, SN, Santiesteban, SN, Li, S, Abrams, D, Alsalmi, S, Androic, D, Aniol, K, Arrington, J, Averett, T, Gayoso, C Ayerbe, Bane, J, Barcus, S, Barrow, J, Beck, A, Bellini, V, Bhatt, H, Bhetuwal, D, Biswas, D, Camsonne, A, Castellanos, J, Chen, J, Chen, J-P, Chrisman, D, Christy, ME, Clarke, C, Covrig, S, Cruz-Torres, R, Day, D, Dutta, D, Fuchey, E, Gal, C, Garibaldi, F, Gautam, TN, Gogami, T, Gomez, J, Guèye, P, Hague, TJ, Hansen, JO, Hauenstein, F, Henry, W, Higinbotham, DW, Holt, RJ, Hyde, C, Itabashi, K, Kaneta, M, Karki, A, Katramatou, AT, Keppel, CE, King, PM, Kurbany, L, Kutz, T, Lashley-Colthirst, N, Li, WB, Liu, H, Liyanage, N, Long, E, Lovato, A, Mammei, J, Markowitz, P, McClellan, RE, Meddi, F, Meekins, D, Michaels, R, Mihovilovič, M, Moyer, A, Nagao, S, Nguyen, D, Nycz, M, Olson, M, Ou, L, Owen, V, Palatchi, C, Pandey, B, Papadopoulou, A, Park, S, Petkovic, T, Premathilake, S, Punjabi, V, Ransome, RD, Reimer, PE, Reinhold, J, Riordan, S, Rocco, N, Rodriguez, VM, Schmidt, A, Schmookler, B, Segarra, EP, Shahinyan, A, Širca, S, Slifer, K, Solvignon, P, Su, T, Suleiman, R, Tang, L, Tian, Y, Tireman, W, Tortorici, F, Toyama, Y, Uehara, K, Urciuoli, GM, Votaw, D, Santiesteban, SN, Santiesteban, SN, Li, S, Abrams, D, Alsalmi, S, Androic, D, Aniol, K, Arrington, J, Averett, T, Gayoso, C Ayerbe, Bane, J, Barcus, S, Barrow, J, Beck, A, Bellini, V, Bhatt, H, Bhetuwal, D, Biswas, D, Camsonne, A, Castellanos, J, Chen, J, Chen, J-P, Chrisman, D, Christy, ME, Clarke, C, Covrig, S, Cruz-Torres, R, Day, D, Dutta, D, Fuchey, E, Gal, C, Garibaldi, F, Gautam, TN, Gogami, T, Gomez, J, Guèye, P, Hague, TJ, Hansen, JO, Hauenstein, F, Henry, W, Higinbotham, DW, Holt, RJ, Hyde, C, Itabashi, K, Kaneta, M, Karki, A, Katramatou, AT, Keppel, CE, King, PM, Kurbany, L, Kutz, T, Lashley-Colthirst, N, Li, WB, Liu, H, Liyanage, N, Long, E, Lovato, A, Mammei, J, Markowitz, P, McClellan, RE, Meddi, F, Meekins, D, Michaels, R, Mihovilovič, M, Moyer, A, Nagao, S, Nguyen, D, Nycz, M, Olson, M, Ou, L, Owen, V, Palatchi, C, Pandey, B, Papadopoulou, A, Park, S, Petkovic, T, Premathilake, S, Punjabi, V, Ransome, RD, Reimer, PE, Reinhold, J, Riordan, S, Rocco, N, Rodriguez, VM, Schmidt, A, Schmookler, B, Segarra, EP, Shahinyan, A, Širca, S, Slifer, K, Solvignon, P, Su, T, Suleiman, R, Tang, L, Tian, Y, Tireman, W, Tortorici, F, Toyama, Y, Uehara, K, Urciuoli, GM, and Votaw, D
Abstract: The electromagnetic form factors of the proton and neutron encode information on the spatial structure of their charge and magnetization distributions. While measurements of the proton are relatively straightforward, the lack of a free neutron target makes measurements of the neutron's electromagnetic structure more challenging and more sensitive to experimental or model-dependent uncertainties. Various experiments have attempted to extract the neutron form factors from scattering from the neutron in deuterium, with different techniques providing different, and sometimes large, systematic uncertainties. We present results from a novel measurement of the neutron magnetic form factor using quasielastic scattering from the mirror nuclei ^{3}H and ^{3}He, where the nuclear effects are larger than for deuterium but expected to largely cancel in the cross-section ratios. We extracted values of the neutron magnetic form factor for low-to-modest momentum transfer, 0.6
Published: 2024

2. A Synthesis of Global Coastal Ocean Greenhouse Gas Fluxes

Author: Resplandy, L, Hogikyan, A, Müller, JD, Najjar, RG, Bange, HW, Bianchi, D, Weber, T, Cai, W‐J, Doney, SC, Fennel, K, Gehlen, M, Hauck, J, Lacroix, F, Landschützer, P, Le Quéré, C, Roobaert, A, Schwinger, J, Berthet, S, Bopp, L, Chau, TTT, Dai, M, Gruber, N, Ilyina, T, Kock, A, Manizza, M, Lachkar, Z, Laruelle, GG, Liao, E, Lima, ID, Nissen, Cara, Rödenbeck, C, Séférian, R, Toyama, K, Tsujino, H, Regnier, P, Resplandy, L, Hogikyan, A, Müller, JD, Najjar, RG, Bange, HW, Bianchi, D, Weber, T, Cai, W‐J, Doney, SC, Fennel, K, Gehlen, M, Hauck, J, Lacroix, F, Landschützer, P, Le Quéré, C, Roobaert, A, Schwinger, J, Berthet, S, Bopp, L, Chau, TTT, Dai, M, Gruber, N, Ilyina, T, Kock, A, Manizza, M, Lachkar, Z, Laruelle, GG, Liao, E, Lima, ID, Nissen, Cara, Rödenbeck, C, Séférian, R, Toyama, K, Tsujino, H, and Regnier, P
Abstract: The coastal ocean contributes to regulating atmospheric greenhouse gas concentrations by taking up carbon dioxide (CO2) and releasing nitrous oxide (N2O) and methane (CH4). In this second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP2), we quantify global coastal ocean fluxes of CO2, N2O and CH4 using an ensemble of global gap-filled observation-based products and ocean biogeochemical models. The global coastal ocean is a net sink of CO2 in both observational products and models, but the magnitude of the median net global coastal uptake is ∼60% larger in models (−0.72 vs. −0.44 PgC year−1, 1998–2018, coastal ocean extending to 300 km offshore or 1,000 m isobath with area of 77 million km2). We attribute most of this model-product difference to the seasonality in sea surface CO2 partial pressure at mid- and high-latitudes, where models simulate stronger winter CO2 uptake. The coastal ocean CO2 sink has increased in the past decades but the available time-resolving observation-based products and models show large discrepancies in the magnitude of this increase. The global coastal ocean is a major source of N2O (+0.70 PgCO2-e year−1 in observational product and +0.54 PgCO2-e year−1 in model median) and CH4 (+0.21 PgCO2-e year−1 in observational product), which offsets a substantial proportion of the coastal CO2 uptake in the net radiative balance (30%–60% in CO2-equivalents), highlighting the importance of considering the three greenhouse gases when examining the influence of the coastal ocean on climate.
Published: 2024

3. Starobinsky inflation beyond the leading order

Author: Toyama, Shunsuke, Ketov, Sergei V., Toyama, Shunsuke, and Ketov, Sergei V.
Abstract: The Starobinsky model of cosmological inflation in four spacetime dimensions is reviewed with the emphasis on impact of quantum gravity corrections. As a specific example of the quantum corrections, the Grisaru-Zanon quartic curvature terms in the gravitational effective action of closed superstrings are chosen. Those quartic curvature terms are compared to the Bel-Robinson tensor squared in a flat Friedman universe, and the upper bound on the effective string coupling constant is found by demanding unitarity (causality) and the absence of ghosts. It is found that the quantum corrections to the observables (tilts) of the cosmic microwave background radiation in the Starobinsky inflation may be of the same order of magnitude as the next-to-next-to-next classical contributions in the Starobinsky model with respect to the inverse powers of the e-folding number at the horizon crossing., Comment: 13 pages, no figures, LaTeX; a reference added
Published: 2024

4. A Synthesis of Global Coastal Ocean Greenhouse Gas Fluxes

Author: Resplandy, L., Hogikyan, A., Müller, J. D., Najjar, R. G., Bange, Hermann W., Bianchi, D., Weber, T., Cai, W.‐J., Doney, S. C., Fennel, K., Gehlen, M., Hauck, J., Lacroix, F., Landschützer, P., Le Quéré, C., Roobaert, A., Schwinger, J., Berthet, S., Bopp, L., Chau, T. T. T., Dai, M., Gruber, N., Ilyina, T., Kock, Annette, Manizza, M., Lachkar, Z., Laruelle, G. G., Liao, E., Lima, I. D., Nissen, C., Rödenbeck, C., Séférian, R., Toyama, K., Tsujino, H., Regnier, P., Resplandy, L., Hogikyan, A., Müller, J. D., Najjar, R. G., Bange, Hermann W., Bianchi, D., Weber, T., Cai, W.‐J., Doney, S. C., Fennel, K., Gehlen, M., Hauck, J., Lacroix, F., Landschützer, P., Le Quéré, C., Roobaert, A., Schwinger, J., Berthet, S., Bopp, L., Chau, T. T. T., Dai, M., Gruber, N., Ilyina, T., Kock, Annette, Manizza, M., Lachkar, Z., Laruelle, G. G., Liao, E., Lima, I. D., Nissen, C., Rödenbeck, C., Séférian, R., Toyama, K., Tsujino, H., and Regnier, P.
Abstract: The coastal ocean contributes to regulating atmospheric greenhouse gas concentrations by taking up carbon dioxide (CO2) and releasing nitrous oxide (N2O) and methane (CH4). In this second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP2), we quantify global coastal ocean fluxes of CO2, N2O and CH4 using an ensemble of global gap-filled observation-based products and ocean biogeochemical models. The global coastal ocean is a net sink of CO2 in both observational products and models, but the magnitude of the median net global coastal uptake is similar to 60% larger in models (-0.72 vs. -0.44 PgC year-1, 1998-2018, coastal ocean extending to 300 km offshore or 1,000 m isobath with area of 77 million km2). We attribute most of this model-product difference to the seasonality in sea surface CO2 partial pressure at mid- and high-latitudes, where models simulate stronger winter CO2 uptake. The coastal ocean CO2 sink has increased in the past decades but the available time-resolving observation-based products and models show large discrepancies in the magnitude of this increase. The global coastal ocean is a major source of N2O (+0.70 PgCO2-e year-1 in observational product and +0.54 PgCO2-e year-1 in model median) and CH4 (+0.21 PgCO2-e year-1 in observational product), which offsets a substantial proportion of the coastal CO2 uptake in the net radiative balance (30%-60% in CO2-equivalents), highlighting the importance of considering the three greenhouse gases when examining the influence of the coastal ocean on climate. The coastal ocean regulates greenhouse gases. It acts as a sink of carbon dioxide (CO2) but also releases nitrous oxide (N2O) and methane (CH4) into the atmosphere. This synthesis contributes to the second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP2) and provides a comprehensive view of the coastal air-sea fluxes of these three greenhouse gases at the global scale. We use a multi-faceted approach combining gap-f
Published: 2024
Full Text: View/download PDF

5. A Synthesis of Global Coastal Ocean Greenhouse Gas Fluxes

Author: Resplandy, Laure LR, Hogikyan, A., Müller, Jens Daniel, Najjar, Raymond R.G., Hermann, W. Bange, Bianchi, Daniele, Weber, T., Cai, Wei-Jun, Doney, S. C., Fennel, Katja, Gehlen, Marion, Hauck, J., Lacroix, Fabrice, Landschutzer, Peter, Le Quéré, Corinne, Roobaert, Alizée, Schwinger, J., Berthet, Sarah, Bopp, Laurent, Chau, Thi T. T., Dai, Minhan, Gruber, Nicolas, Ilyina, Tatiana, Kock, A., Manizza, M., Lachkar, Z., Laruelle, Goulven Gildas, Liao, Enhui EL, Lima, I. D., Nissen, C, Rödenbeck, Christian, Séférian, Roland, Toyama, K., Tsujino, H., Regnier, Pierre A.G., Resplandy, Laure LR, Hogikyan, A., Müller, Jens Daniel, Najjar, Raymond R.G., Hermann, W. Bange, Bianchi, Daniele, Weber, T., Cai, Wei-Jun, Doney, S. C., Fennel, Katja, Gehlen, Marion, Hauck, J., Lacroix, Fabrice, Landschutzer, Peter, Le Quéré, Corinne, Roobaert, Alizée, Schwinger, J., Berthet, Sarah, Bopp, Laurent, Chau, Thi T. T., Dai, Minhan, Gruber, Nicolas, Ilyina, Tatiana, Kock, A., Manizza, M., Lachkar, Z., Laruelle, Goulven Gildas, Liao, Enhui EL, Lima, I. D., Nissen, C, Rödenbeck, Christian, Séférian, Roland, Toyama, K., Tsujino, H., and Regnier, Pierre A.G.
Abstract: The coastal ocean contributes to regulating atmospheric greenhouse gas concentrations by taking up carbon dioxide (CO2) and releasing nitrous oxide (N2O) and methane (CH4). In this second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP2), we quantify global coastal ocean fluxes of CO2, N2O and CH4 using an ensemble of global gap-filled observation-based products and ocean biogeochemical models. The global coastal ocean is a net sink of CO2 in both observational products and models, but the magnitude of the median net global coastal uptake is ∼60% larger in models (−0.72 vs. −0.44 PgC year−1, 1998–2018, coastal ocean extending to 300 km offshore or 1,000 m isobath with area of 77 million km2). We attribute most of this model-product difference to the seasonality in sea surface CO2 partial pressure at mid- and high-latitudes, where models simulate stronger winter CO2 uptake. The coastal ocean CO2 sink has increased in the past decades but the available time-resolving observation-based products and models show large discrepancies in the magnitude of this increase. The global coastal ocean is a major source of N2O (+0.70 PgCO2-e year−1 in observational product and +0.54 PgCO2-e year−1 in model median) and CH4 (+0.21 PgCO2-e year−1 in observational product), which offsets a substantial proportion of the coastal CO2 uptake in the net radiative balance (30%–60% in CO2-equivalents), highlighting the importance of considering the three greenhouse gases when examining the influence of the coastal ocean on climate., SCOPUS: ar.j, info:eu-repo/semantics/published
Published: 2024

6. A Synthesis of Global Coastal Ocean Greenhouse Gas Fluxes

Author: Resplandy, L., Hogikyan, A., Müller, J. D., Najjar, R. G., Bange, Hermann W., Bianchi, D., Weber, T., Cai, W.‐J., Doney, S. C., Fennel, K., Gehlen, M., Hauck, J., Lacroix, F., Landschützer, P., Le Quéré, C., Roobaert, A., Schwinger, J., Berthet, S., Bopp, L., Chau, T. T. T., Dai, M., Gruber, N., Ilyina, T., Kock, Annette, Manizza, M., Lachkar, Z., Laruelle, G. G., Liao, E., Lima, I. D., Nissen, C., Rödenbeck, C., Séférian, R., Toyama, K., Tsujino, H., Regnier, P., Resplandy, L., Hogikyan, A., Müller, J. D., Najjar, R. G., Bange, Hermann W., Bianchi, D., Weber, T., Cai, W.‐J., Doney, S. C., Fennel, K., Gehlen, M., Hauck, J., Lacroix, F., Landschützer, P., Le Quéré, C., Roobaert, A., Schwinger, J., Berthet, S., Bopp, L., Chau, T. T. T., Dai, M., Gruber, N., Ilyina, T., Kock, Annette, Manizza, M., Lachkar, Z., Laruelle, G. G., Liao, E., Lima, I. D., Nissen, C., Rödenbeck, C., Séférian, R., Toyama, K., Tsujino, H., and Regnier, P.
Abstract: The coastal ocean contributes to regulating atmospheric greenhouse gas concentrations by taking up carbon dioxide (CO2) and releasing nitrous oxide (N2O) and methane (CH4). In this second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP2), we quantify global coastal ocean fluxes of CO2, N2O and CH4 using an ensemble of global gap-filled observation-based products and ocean biogeochemical models. The global coastal ocean is a net sink of CO2 in both observational products and models, but the magnitude of the median net global coastal uptake is similar to 60% larger in models (-0.72 vs. -0.44 PgC year-1, 1998-2018, coastal ocean extending to 300 km offshore or 1,000 m isobath with area of 77 million km2). We attribute most of this model-product difference to the seasonality in sea surface CO2 partial pressure at mid- and high-latitudes, where models simulate stronger winter CO2 uptake. The coastal ocean CO2 sink has increased in the past decades but the available time-resolving observation-based products and models show large discrepancies in the magnitude of this increase. The global coastal ocean is a major source of N2O (+0.70 PgCO2-e year-1 in observational product and +0.54 PgCO2-e year-1 in model median) and CH4 (+0.21 PgCO2-e year-1 in observational product), which offsets a substantial proportion of the coastal CO2 uptake in the net radiative balance (30%-60% in CO2-equivalents), highlighting the importance of considering the three greenhouse gases when examining the influence of the coastal ocean on climate. The coastal ocean regulates greenhouse gases. It acts as a sink of carbon dioxide (CO2) but also releases nitrous oxide (N2O) and methane (CH4) into the atmosphere. This synthesis contributes to the second phase of the Regional Carbon Cycle Assessment and Processes (RECCAP2) and provides a comprehensive view of the coastal air-sea fluxes of these three greenhouse gases at the global scale. We use a multi-faceted approach combining gap-f
Published: 2024
Full Text: View/download PDF

7. Measuring Patient-Reported Use and Outcomes From Complementary and Integrative Health Therapies: Development of the Complementary and Integrative Health Therapy Patient Experience Survey.

Author: Elwy, A, Elwy, A, Bokhour, Barbara, Coggeshall, Scott, Cohen, Amy, Der-Martirosian, Claudia, Haderlein, Taona, Haun, Jolie, Kligler, Benjamin, Kloehn, Alex, Lorenz, Karl, Lott, Briana, Shin, Marlena, Schult, Tammy, Toyama, Joy, Whitehead, Alison, Zhang, Xiaoyi, Zeliadt, Steven, Taylor, Stephanie, Elwy, A, Elwy, A, Bokhour, Barbara, Coggeshall, Scott, Cohen, Amy, Der-Martirosian, Claudia, Haderlein, Taona, Haun, Jolie, Kligler, Benjamin, Kloehn, Alex, Lorenz, Karl, Lott, Briana, Shin, Marlena, Schult, Tammy, Toyama, Joy, Whitehead, Alison, Zhang, Xiaoyi, Zeliadt, Steven, and Taylor, Stephanie
Abstract: BACKGROUND: Assessing the use and effectiveness of complementary and integrative health (CIH) therapies via survey can be complicated given CIH therapies are used in various locations and formats, the dosing required to have an effect is unclear, the potential health and well-being outcomes are many, and describing CIH therapies can be challenging. Few surveys assessing CIH therapy use and effectiveness exist, and none sufficiently reflect these complexities. OBJECTIVE: In a large-scale Veterans Health Administration (VA) quality improvement effort, we developed the Complementary and Integrative Health Therapy Patient Experience Survey, a longitudinal, electronic patient self-administered survey to comprehensively assess CIH therapy use and outcomes. METHODS: We obtained guidance from the literature, subject matter experts, and Veteran patients who used CIH therapies in designing the survey. As a validity check, we completed cognitive testing and interviews with those patients. We conducted the survey (March 2021-April 2023), inviting 15,608 Veterans with chronic musculoskeletal pain with a recent CIH appointment or referral identified in VA electronic medical records (EMR) to participate. As a second validity check, we compared VA EMR data and patient self-reports of CIH therapy utilization a month after survey initiation and again at survey conclusion. RESULTS: The 64-item, electronic survey assesses CIH dosing (amount and timing), delivery format and location, provider location, and payor. It also assesses 7 patient-reported outcomes (pain, global mental health, global physical health, depression, quality of life, stress, and meaning/purpose in life), and 3 potential mediators (perceived health competency, healthcare engagement, and self-efficacy for managing diseases). The survey took 17 minutes on average to complete and had a baseline response rate of 45.3%. We found high degrees of concordance between self-reported and EMR data for all therapies except m
Published: 2024

8. Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Author: Gemini Team, Reid, Machel, Savinov, Nikolay, Teplyashin, Denis, Dmitry, Lepikhin, Lillicrap, Timothy, Alayrac, Jean-baptiste, Soricut, Radu, Lazaridou, Angeliki, Firat, Orhan, Schrittwieser, Julian, Antonoglou, Ioannis, Anil, Rohan, Borgeaud, Sebastian, Dai, Andrew, Millican, Katie, Dyer, Ethan, Glaese, Mia, Sottiaux, Thibault, Lee, Benjamin, Viola, Fabio, Reynolds, Malcolm, Xu, Yuanzhong, Molloy, James, Chen, Jilin, Isard, Michael, Barham, Paul, Hennigan, Tom, McIlroy, Ross, Johnson, Melvin, Schalkwyk, Johan, Collins, Eli, Rutherford, Eliza, Moreira, Erica, Ayoub, Kareem, Goel, Megha, Meyer, Clemens, Thornton, Gregory, Yang, Zhen, Michalewski, Henryk, Abbas, Zaheer, Schucher, Nathan, Anand, Ankesh, Ives, Richard, Keeling, James, Lenc, Karel, Haykal, Salem, Shakeri, Siamak, Shyam, Pranav, Chowdhery, Aakanksha, Ring, Roman, Spencer, Stephen, Sezener, Eren, Vilnis, Luke, Chang, Oscar, Morioka, Nobuyuki, Tucker, George, Zheng, Ce, Woodman, Oliver, Attaluri, Nithya, Kocisky, Tomas, Eltyshev, Evgenii, Chen, Xi, Chung, Timothy, Selo, Vittorio, Brahma, Siddhartha, Georgiev, Petko, Slone, Ambrose, Zhu, Zhenkai, Lottes, James, Qiao, Siyuan, Caine, Ben, Riedel, Sebastian, Tomala, Alex, Chadwick, Martin, Love, Juliette, Choy, Peter, Mittal, Sid, Houlsby, Neil, Tang, Yunhao, Lamm, Matthew, Bai, Libin, Zhang, Qiao, He, Luheng, Cheng, Yong, Humphreys, Peter, Li, Yujia, Brin, Sergey, Cassirer, Albin, Miao, Yingjie, Zilka, Lukas, Tobin, Taylor, Xu, Kelvin, Proleev, Lev, Sohn, Daniel, Magni, Alberto, Hendricks, Lisa Anne, Gao, Isabel, Ontanon, Santiago, Bunyan, Oskar, Byrd, Nathan, Sharma, Abhanshu, Zhang, Biao, Pinto, Mario, Sinha, Rishika, Mehta, Harsh, Jia, Dawei, Caelles, Sergi, Webson, Albert, Morris, Alex, Roelofs, Becca, Ding, Yifan, Strudel, Robin, Xiong, Xuehan, Ritter, Marvin, Dehghani, Mostafa, Chaabouni, Rahma, Karmarkar, Abhijit, Lai, Guangda, Mentzer, Fabian, Xu, Bibo, Li, YaGuang, Zhang, Yujing, Paine, Tom Le, Goldin, Alex, Neyshabur, Behnam, Baumli, Kate, Levskaya, Anselm, Laskin, Michael, Jia, Wenhao, Rae, Jack W., Xiao, Kefan, He, Antoine, Giordano, Skye, Yagati, Lakshman, Lespiau, Jean-Baptiste, Natsev, Paul, Ganapathy, Sanjay, Liu, Fangyu, Martins, Danilo, Chen, Nanxin, Xu, Yunhan, Barnes, Megan, May, Rhys, Vezer, Arpi, Oh, Junhyuk, Franko, Ken, Bridgers, Sophie, Zhao, Ruizhe, Wu, Boxi, Mustafa, Basil, Sechrist, Sean, Parisotto, Emilio, Pillai, Thanumalayan Sankaranarayana, Larkin, Chris, Gu, Chenjie, Sorokin, Christina, Krikun, Maxim, Guseynov, Alexey, Landon, Jessica, Datta, Romina, Pritzel, Alexander, Thacker, Phoebe, Yang, Fan, Hui, Kevin, Hauth, Anja, Yeh, Chih-Kuan, Barker, David, Mao-Jones, Justin, Austin, Sophia, Sheahan, Hannah, Schuh, Parker, Svensson, James, Jain, Rohan, Ramasesh, Vinay, Briukhov, Anton, Chung, Da-Woon, von Glehn, Tamara, Butterfield, Christina, Jhakra, Priya, Wiethoff, Matthew, Frye, Justin, Grimstad, Jordan, Changpinyo, Beer, Lan, Charline Le, Bortsova, Anna, Wu, Yonghui, Voigtlaender, Paul, Sainath, Tara, Gu, Shane, Smith, Charlotte, Hawkins, Will, Cao, Kris, Besley, James, Srinivasan, Srivatsan, Omernick, Mark, Gaffney, Colin, Surita, Gabriela, Burnell, Ryan, Damoc, Bogdan, Ahn, Junwhan, Brock, Andrew, Pajarskas, Mantas, Petrushkina, Anastasia, Noury, Seb, Blanco, Lorenzo, Swersky, Kevin, Ahuja, Arun, Avrahami, Thi, Misra, Vedant, de Liedekerke, Raoul, Iinuma, Mariko, Polozov, Alex, York, Sarah, Driessche, George van den, Michel, Paul, Chiu, Justin, Blevins, Rory, Gleicher, Zach, Recasens, Adrià, Rrustemi, Alban, Gribovskaya, Elena, Roy, Aurko, Gworek, Wiktor, Arnold, Sébastien M. R., Lee, Lisa, Lee-Thorp, James, Maggioni, Marcello, Piqueras, Enrique, Badola, Kartikeya, Vikram, Sharad, Gonzalez, Lucas, Baddepudi, Anirudh, Senter, Evan, Devlin, Jacob, Qin, James, Azzam, Michael, Trebacz, Maja, Polacek, Martin, Krishnakumar, Kashyap, Chang, Shuo-yiin, Tung, Matthew, Penchev, Ivo, Joshi, Rishabh, Olszewska, Kate, Muir, Carrie, Wirth, Mateo, Hartman, Ale Jakse, Newlan, Josh, Kashem, Sheleem, Bolina, Vijay, Dabir, Elahe, van Amersfoort, Joost, Ahmed, Zafarali, Cobon-Kerr, James, Kamath, Aishwarya, Hrafnkelsson, Arnar Mar, Hou, Le, Mackinnon, Ian, Frechette, Alexandre, Noland, Eric, Si, Xiance, Taropa, Emanuel, Li, Dong, Crone, Phil, Gulati, Anmol, Cevey, Sébastien, Adler, Jonas, Ma, Ada, Silver, David, Tokumine, Simon, Powell, Richard, Lee, Stephan, Vodrahalli, Kiran, Hassan, Samer, Mincu, Diana, Yang, Antoine, Levine, Nir, Brennan, Jenny, Wang, Mingqiu, Hodkinson, Sarah, Zhao, Jeffrey, Lipschultz, Josh, Pope, Aedan, Chang, Michael B., Li, Cheng, Shafey, Laurent El, Paganini, Michela, Douglas, Sholto, Bohnet, Bernd, Pardo, Fabio, Odoom, Seth, Rosca, Mihaela, Santos, Cicero Nogueira dos, Soparkar, Kedar, Guez, Arthur, Hudson, Tom, Hansen, Steven, Asawaroengchai, Chulayuth, Addanki, Ravi, Yu, Tianhe, Stokowiec, Wojciech, Khan, Mina, Gilmer, Justin, Lee, Jaehoon, Bostock, Carrie Grimes, Rong, Keran, Caton, Jonathan, Pejman, Pedram, Pavetic, Filip, Brown, Geoff, Sharma, Vivek, Lučić, Mario, Samuel, Rajkumar, Djolonga, Josip, Mandhane, Amol, Sjösund, Lars Lowe, Buchatskaya, Elena, White, Elspeth, Clay, Natalie, Jiang, Jiepu, Lim, Hyeontaek, Hemsley, Ross, Cankara, Zeyncep, Labanowski, Jane, De Cao, Nicola, Steiner, David, Hashemi, Sayed Hadi, Austin, Jacob, Gergely, Anita, Blyth, Tim, Stanton, Joe, Shivakumar, Kaushik, Siddhant, Aditya, Andreassen, Anders, Araya, Carlos, Sethi, Nikhil, Shivanna, Rakesh, Hand, Steven, Bapna, Ankur, Khodaei, Ali, Miech, Antoine, Tanzer, Garrett, Swing, Andy, Thakoor, Shantanu, Aroyo, Lora, Pan, Zhufeng, Nado, Zachary, Sygnowski, Jakub, Winkler, Stephanie, Yu, Dian, Saleh, Mohammad, Maggiore, Loren, Bansal, Yamini, Garcia, Xavier, Kazemi, Mehran, Patil, Piyush, Dasgupta, Ishita, Barr, Iain, Giang, Minh, Kagohara, Thais, Danihelka, Ivo, Marathe, Amit, Feinberg, Vladimir, Elhawaty, Mohamed, Ghelani, Nimesh, Horgan, Dan, Miller, Helen, Walker, Lexi, Tanburn, Richard, Tariq, Mukarram, Shrivastava, Disha, Xia, Fei, Wang, Qingze, Chiu, Chung-Cheng, Ashwood, Zoe, Baatarsukh, Khuslen, Samangooei, Sina, Kaufman, Raphaël Lopez, Alcober, Fred, Stjerngren, Axel, Komarek, Paul, Tsihlas, Katerina, Boral, Anudhyan, Comanescu, Ramona, Chen, Jeremy, Liu, Ruibo, Welty, Chris, Bloxwich, Dawn, Chen, Charlie, Sun, Yanhua, Feng, Fangxiaoyu, Mauger, Matthew, Dotiwalla, Xerxes, Hellendoorn, Vincent, Sharman, Michael, Zheng, Ivy, Haridasan, Krishna, Barth-Maron, Gabe, Swanson, Craig, Rogozińska, Dominika, Andreev, Alek, Rubenstein, Paul Kishan, Sang, Ruoxin, Hurt, Dan, Elsayed, Gamaleldin, Wang, Renshen, Lacey, Dave, Ilić, Anastasija, Zhao, Yao, Iwanicki, Adam, Lince, Alejandro, Chen, Alexander, Lyu, Christina, Lebsack, Carl, Griffith, Jordan, Gaba, Meenu, Sandhu, Paramjit, Chen, Phil, Koop, Anna, Rajwar, Ravi, Yeganeh, Soheil Hassas, Chang, Solomon, Zhu, Rui, Radpour, Soroush, Davoodi, Elnaz, Lei, Ving Ian, Xu, Yang, Toyama, Daniel, Segal, Constant, Wicke, Martin, Lin, Hanzhao, Bulanova, Anna, Badia, Adrià Puigdomènech, Rakićević, Nemanja, Sprechmann, Pablo, Filos, Angelos, Hou, Shaobo, Campos, Víctor, Kassner, Nora, Sachan, Devendra, Fortunato, Meire, Iwuanyanwu, Chimezie, Nikolaev, Vitaly, Lakshminarayanan, Balaji, Jazayeri, Sadegh, Varadarajan, Mani, Tekur, Chetan, Fritz, Doug, Khalman, Misha, Reitter, David, Dasgupta, Kingshuk, Sarcar, Shourya, Ornduff, Tina, Snaider, Javier, Huot, Fantine, Jia, Johnson, Kemp, Rupert, Trdin, Nejc, Vijayakumar, Anitha, Kim, Lucy, Angermueller, Christof, Lao, Li, Liu, Tianqi, Zhang, Haibin, Engel, David, Greene, Somer, White, Anaïs, Austin, Jessica, Taylor, Lilly, Ashraf, Shereen, Liu, Dangyi, Georgaki, Maria, Cai, Irene, Kulizhskaya, Yana, Goenka, Sonam, Saeta, Brennan, Xu, Ying, Frank, Christian, de Cesare, Dario, Robenek, Brona, Richardson, Harry, Alnahlawi, Mahmoud, Yew, Christopher, Ponnapalli, Priya, Tagliasacchi, Marco, Korchemniy, Alex, Kim, Yelin, Li, Dinghua, Rosgen, Bill, Levin, Kyle, Wiesner, Jeremy, Banzal, Praseem, Srinivasan, Praveen, Yu, Hongkun, Ünlü, Çağlar, Reid, David, Tung, Zora, Finchelstein, Daniel, Kumar, Ravin, Elisseeff, Andre, Huang, Jin, Zhang, Ming, Aguilar, Ricardo, Giménez, Mai, Xia, Jiawei, Dousse, Olivier, Gierke, Willi, Yates, Damion, Jalan, Komal, Li, Lu, Latorre-Chimoto, Eri, Nguyen, Duc Dung, Durden, Ken, Kallakuri, Praveen, Liu, Yaxin, Johnson, Matthew, Tsai, Tomy, Talbert, Alice, Liu, Jasmine, Neitz, Alexander, Elkind, Chen, Selvi, Marco, Jasarevic, Mimi, Soares, Livio Baldini, Cui, Albert, Wang, Pidong, Wang, Alek Wenjiao, Ye, Xinyu, Kallarackal, Krystal, Loher, Lucia, Lam, Hoi, Broder, Josef, Holtmann-Rice, Dan, Martin, Nina, Ramadhana, Bramandia, Shukla, Mrinal, Basu, Sujoy, Mohan, Abhi, Fernando, Nick, Fiedel, Noah, Paterson, Kim, Li, Hui, Garg, Ankush, Park, Jane, Choi, DongHyun, Wu, Diane, Singh, Sankalp, Zhang, Zhishuai, Globerson, Amir, Yu, Lily, Carpenter, John, Quitry, Félix de Chaumont, Radebaugh, Carey, Lin, Chu-Cheng, Tudor, Alex, Shroff, Prakash, Garmon, Drew, Du, Dayou, Vats, Neera, Lu, Han, Iqbal, Shariq, Yakubovich, Alex, Tripuraneni, Nilesh, Manyika, James, Qureshi, Haroon, Hua, Nan, Ngani, Christel, Raad, Maria Abi, Forbes, Hannah, Stanway, Jeff, Sundararajan, Mukund, Ungureanu, Victor, Bishop, Colton, Li, Yunjie, Venkatraman, Balaji, Li, Bo, Thornton, Chloe, Scellato, Salvatore, Gupta, Nishesh, Wang, Yicheng, Tenney, Ian, Wu, Xihui, Shenoy, Ashish, Carvajal, Gabriel, Wright, Diana Gage, Bariach, Ben, Xiao, Zhuyun, Hawkins, Peter, Dalmia, Sid, Farabet, Clement, Valenzuela, Pedro, Yuan, Quan, Agarwal, Ananth, Chen, Mia, Kim, Wooyeol, Hulse, Brice, Dukkipati, Nandita, Paszke, Adam, Bolt, Andrew, Choo, Kiam, Beattie, Jennifer, Prendki, Jennifer, Vashisht, Harsha, Santamaria-Fernandez, Rebeca, Cobo, Luis C., Wilkiewicz, Jarek, Madras, David, Elqursh, Ali, Uy, Grant, Ramirez, Kevin, Harvey, Matt, Liechty, Tyler, Zen, Heiga, Seibert, Jeff, Hu, Clara Huiyi, Khorlin, Andrey, Le, Maigo, Aharoni, Asaf, Li, Megan, Wang, Lily, Kumar, Sandeep, Casagrande, Norman, Hoover, Jay, Badawy, Dalia El, Soergel, David, Vnukov, Denis, Miecnikowski, Matt, Simsa, Jiri, Kumar, Praveen, Sellam, Thibault, Vlasic, Daniel, Daruki, Samira, Shabat, Nir, Zhang, John, Su, Guolong, Zhang, Jiageng, Liu, Jeremiah, Sun, Yi, Palmer, Evan, Ghaffarkhah, Alireza, Xiong, Xi, Cotruta, Victor, Fink, Michael, Dixon, Lucas, Sreevatsa, Ashwin, Goedeckemeyer, Adrian, Dimitriev, Alek, Jafari, Mohsen, Crocker, Remi, FitzGerald, Nicholas, Kumar, Aviral, Ghemawat, Sanjay, Philips, Ivan, Liu, Frederick, Liang, Yannie, Sterneck, Rachel, Repina, Alena, Wu, Marcus, Knight, Laura, Georgiev, Marin, Lee, Hyo, Askham, Harry, Chakladar, Abhishek, Louis, Annie, Crous, Carl, Cate, Hardie, Petrova, Dessie, Quinn, Michael, Owusu-Afriyie, Denese, Singhal, Achintya, Wei, Nan, Kim, Solomon, Vincent, Damien, Nasr, Milad, Choquette-Choo, Christopher A., Tojo, Reiko, Lu, Shawn, Casas, Diego de Las, Cheng, Yuchung, Bolukbasi, Tolga, Lee, Katherine, Fatehi, Saaber, Ananthanarayanan, Rajagopal, Patel, Miteyan, Kaed, Charbel, Li, Jing, Belle, Shreyas Rammohan, Chen, Zhe, Konzelmann, Jaclyn, Põder, Siim, Garg, Roopal, Koverkathu, Vinod, Brown, Adam, Dyer, Chris, Liu, Rosanne, Nova, Azade, Xu, Jun, Walton, Alanna, Parrish, Alicia, Epstein, Mark, McCarthy, Sara, Petrov, Slav, Hassabis, Demis, Kavukcuoglu, Koray, Dean, Jeffrey, Vinyals, Oriol, Gemini Team, Reid, Machel, Savinov, Nikolay, Teplyashin, Denis, Dmitry, Lepikhin, Lillicrap, Timothy, Alayrac, Jean-baptiste, Soricut, Radu, Lazaridou, Angeliki, Firat, Orhan, Schrittwieser, Julian, Antonoglou, Ioannis, Anil, Rohan, Borgeaud, Sebastian, Dai, Andrew, Millican, Katie, Dyer, Ethan, Glaese, Mia, Sottiaux, Thibault, Lee, Benjamin, Viola, Fabio, Reynolds, Malcolm, Xu, Yuanzhong, Molloy, James, Chen, Jilin, Isard, Michael, Barham, Paul, Hennigan, Tom, McIlroy, Ross, Johnson, Melvin, Schalkwyk, Johan, Collins, Eli, Rutherford, Eliza, Moreira, Erica, Ayoub, Kareem, Goel, Megha, Meyer, Clemens, Thornton, Gregory, Yang, Zhen, Michalewski, Henryk, Abbas, Zaheer, Schucher, Nathan, Anand, Ankesh, Ives, Richard, Keeling, James, Lenc, Karel, Haykal, Salem, Shakeri, Siamak, Shyam, Pranav, Chowdhery, Aakanksha, Ring, Roman, Spencer, Stephen, Sezener, Eren, Vilnis, Luke, Chang, Oscar, Morioka, Nobuyuki, Tucker, George, Zheng, Ce, Woodman, Oliver, Attaluri, Nithya, Kocisky, Tomas, Eltyshev, Evgenii, Chen, Xi, Chung, Timothy, Selo, Vittorio, Brahma, Siddhartha, Georgiev, Petko, Slone, Ambrose, Zhu, Zhenkai, Lottes, James, Qiao, Siyuan, Caine, Ben, Riedel, Sebastian, Tomala, Alex, Chadwick, Martin, Love, Juliette, Choy, Peter, Mittal, Sid, Houlsby, Neil, Tang, Yunhao, Lamm, Matthew, Bai, Libin, Zhang, Qiao, He, Luheng, Cheng, Yong, Humphreys, Peter, Li, Yujia, Brin, Sergey, Cassirer, Albin, Miao, Yingjie, Zilka, Lukas, Tobin, Taylor, Xu, Kelvin, Proleev, Lev, Sohn, Daniel, Magni, Alberto, Hendricks, Lisa Anne, Gao, Isabel, Ontanon, Santiago, Bunyan, Oskar, Byrd, Nathan, Sharma, Abhanshu, Zhang, Biao, Pinto, Mario, Sinha, Rishika, Mehta, Harsh, Jia, Dawei, Caelles, Sergi, Webson, Albert, Morris, Alex, Roelofs, Becca, Ding, Yifan, Strudel, Robin, Xiong, Xuehan, Ritter, Marvin, Dehghani, Mostafa, Chaabouni, Rahma, Karmarkar, Abhijit, Lai, Guangda, Mentzer, Fabian, Xu, Bibo, Li, YaGuang, Zhang, Yujing, Paine, Tom Le, Goldin, Alex, Neyshabur, Behnam, Baumli, Kate, Levskaya, Anselm, Laskin, Michael, Jia, Wenhao, Rae, Jack W., Xiao, Kefan, He, Antoine, Giordano, Skye, Yagati, Lakshman, Lespiau, Jean-Baptiste, Natsev, Paul, Ganapathy, Sanjay, Liu, Fangyu, Martins, Danilo, Chen, Nanxin, Xu, Yunhan, Barnes, Megan, May, Rhys, Vezer, Arpi, Oh, Junhyuk, Franko, Ken, Bridgers, Sophie, Zhao, Ruizhe, Wu, Boxi, Mustafa, Basil, Sechrist, Sean, Parisotto, Emilio, Pillai, Thanumalayan Sankaranarayana, Larkin, Chris, Gu, Chenjie, Sorokin, Christina, Krikun, Maxim, Guseynov, Alexey, Landon, Jessica, Datta, Romina, Pritzel, Alexander, Thacker, Phoebe, Yang, Fan, Hui, Kevin, Hauth, Anja, Yeh, Chih-Kuan, Barker, David, Mao-Jones, Justin, Austin, Sophia, Sheahan, Hannah, Schuh, Parker, Svensson, James, Jain, Rohan, Ramasesh, Vinay, Briukhov, Anton, Chung, Da-Woon, von Glehn, Tamara, Butterfield, Christina, Jhakra, Priya, Wiethoff, Matthew, Frye, Justin, Grimstad, Jordan, Changpinyo, Beer, Lan, Charline Le, Bortsova, Anna, Wu, Yonghui, Voigtlaender, Paul, Sainath, Tara, Gu, Shane, Smith, Charlotte, Hawkins, Will, Cao, Kris, Besley, James, Srinivasan, Srivatsan, Omernick, Mark, Gaffney, Colin, Surita, Gabriela, Burnell, Ryan, Damoc, Bogdan, Ahn, Junwhan, Brock, Andrew, Pajarskas, Mantas, Petrushkina, Anastasia, Noury, Seb, Blanco, Lorenzo, Swersky, Kevin, Ahuja, Arun, Avrahami, Thi, Misra, Vedant, de Liedekerke, Raoul, Iinuma, Mariko, Polozov, Alex, York, Sarah, Driessche, George van den, Michel, Paul, Chiu, Justin, Blevins, Rory, Gleicher, Zach, Recasens, Adrià, Rrustemi, Alban, Gribovskaya, Elena, Roy, Aurko, Gworek, Wiktor, Arnold, Sébastien M. R., Lee, Lisa, Lee-Thorp, James, Maggioni, Marcello, Piqueras, Enrique, Badola, Kartikeya, Vikram, Sharad, Gonzalez, Lucas, Baddepudi, Anirudh, Senter, Evan, Devlin, Jacob, Qin, James, Azzam, Michael, Trebacz, Maja, Polacek, Martin, Krishnakumar, Kashyap, Chang, Shuo-yiin, Tung, Matthew, Penchev, Ivo, Joshi, Rishabh, Olszewska, Kate, Muir, Carrie, Wirth, Mateo, Hartman, Ale Jakse, Newlan, Josh, Kashem, Sheleem, Bolina, Vijay, Dabir, Elahe, van Amersfoort, Joost, Ahmed, Zafarali, Cobon-Kerr, James, Kamath, Aishwarya, Hrafnkelsson, Arnar Mar, Hou, Le, Mackinnon, Ian, Frechette, Alexandre, Noland, Eric, Si, Xiance, Taropa, Emanuel, Li, Dong, Crone, Phil, Gulati, Anmol, Cevey, Sébastien, Adler, Jonas, Ma, Ada, Silver, David, Tokumine, Simon, Powell, Richard, Lee, Stephan, Vodrahalli, Kiran, Hassan, Samer, Mincu, Diana, Yang, Antoine, Levine, Nir, Brennan, Jenny, Wang, Mingqiu, Hodkinson, Sarah, Zhao, Jeffrey, Lipschultz, Josh, Pope, Aedan, Chang, Michael B., Li, Cheng, Shafey, Laurent El, Paganini, Michela, Douglas, Sholto, Bohnet, Bernd, Pardo, Fabio, Odoom, Seth, Rosca, Mihaela, Santos, Cicero Nogueira dos, Soparkar, Kedar, Guez, Arthur, Hudson, Tom, Hansen, Steven, Asawaroengchai, Chulayuth, Addanki, Ravi, Yu, Tianhe, Stokowiec, Wojciech, Khan, Mina, Gilmer, Justin, Lee, Jaehoon, Bostock, Carrie Grimes, Rong, Keran, Caton, Jonathan, Pejman, Pedram, Pavetic, Filip, Brown, Geoff, Sharma, Vivek, Lučić, Mario, Samuel, Rajkumar, Djolonga, Josip, Mandhane, Amol, Sjösund, Lars Lowe, Buchatskaya, Elena, White, Elspeth, Clay, Natalie, Jiang, Jiepu, Lim, Hyeontaek, Hemsley, Ross, Cankara, Zeyncep, Labanowski, Jane, De Cao, Nicola, Steiner, David, Hashemi, Sayed Hadi, Austin, Jacob, Gergely, Anita, Blyth, Tim, Stanton, Joe, Shivakumar, Kaushik, Siddhant, Aditya, Andreassen, Anders, Araya, Carlos, Sethi, Nikhil, Shivanna, Rakesh, Hand, Steven, Bapna, Ankur, Khodaei, Ali, Miech, Antoine, Tanzer, Garrett, Swing, Andy, Thakoor, Shantanu, Aroyo, Lora, Pan, Zhufeng, Nado, Zachary, Sygnowski, Jakub, Winkler, Stephanie, Yu, Dian, Saleh, Mohammad, Maggiore, Loren, Bansal, Yamini, Garcia, Xavier, Kazemi, Mehran, Patil, Piyush, Dasgupta, Ishita, Barr, Iain, Giang, Minh, Kagohara, Thais, Danihelka, Ivo, Marathe, Amit, Feinberg, Vladimir, Elhawaty, Mohamed, Ghelani, Nimesh, Horgan, Dan, Miller, Helen, Walker, Lexi, Tanburn, Richard, Tariq, Mukarram, Shrivastava, Disha, Xia, Fei, Wang, Qingze, Chiu, Chung-Cheng, Ashwood, Zoe, Baatarsukh, Khuslen, Samangooei, Sina, Kaufman, Raphaël Lopez, Alcober, Fred, Stjerngren, Axel, Komarek, Paul, Tsihlas, Katerina, Boral, Anudhyan, Comanescu, Ramona, Chen, Jeremy, Liu, Ruibo, Welty, Chris, Bloxwich, Dawn, Chen, Charlie, Sun, Yanhua, Feng, Fangxiaoyu, Mauger, Matthew, Dotiwalla, Xerxes, Hellendoorn, Vincent, Sharman, Michael, Zheng, Ivy, Haridasan, Krishna, Barth-Maron, Gabe, Swanson, Craig, Rogozińska, Dominika, Andreev, Alek, Rubenstein, Paul Kishan, Sang, Ruoxin, Hurt, Dan, Elsayed, Gamaleldin, Wang, Renshen, Lacey, Dave, Ilić, Anastasija, Zhao, Yao, Iwanicki, Adam, Lince, Alejandro, Chen, Alexander, Lyu, Christina, Lebsack, Carl, Griffith, Jordan, Gaba, Meenu, Sandhu, Paramjit, Chen, Phil, Koop, Anna, Rajwar, Ravi, Yeganeh, Soheil Hassas, Chang, Solomon, Zhu, Rui, Radpour, Soroush, Davoodi, Elnaz, Lei, Ving Ian, Xu, Yang, Toyama, Daniel, Segal, Constant, Wicke, Martin, Lin, Hanzhao, Bulanova, Anna, Badia, Adrià Puigdomènech, Rakićević, Nemanja, Sprechmann, Pablo, Filos, Angelos, Hou, Shaobo, Campos, Víctor, Kassner, Nora, Sachan, Devendra, Fortunato, Meire, Iwuanyanwu, Chimezie, Nikolaev, Vitaly, Lakshminarayanan, Balaji, Jazayeri, Sadegh, Varadarajan, Mani, Tekur, Chetan, Fritz, Doug, Khalman, Misha, Reitter, David, Dasgupta, Kingshuk, Sarcar, Shourya, Ornduff, Tina, Snaider, Javier, Huot, Fantine, Jia, Johnson, Kemp, Rupert, Trdin, Nejc, Vijayakumar, Anitha, Kim, Lucy, Angermueller, Christof, Lao, Li, Liu, Tianqi, Zhang, Haibin, Engel, David, Greene, Somer, White, Anaïs, Austin, Jessica, Taylor, Lilly, Ashraf, Shereen, Liu, Dangyi, Georgaki, Maria, Cai, Irene, Kulizhskaya, Yana, Goenka, Sonam, Saeta, Brennan, Xu, Ying, Frank, Christian, de Cesare, Dario, Robenek, Brona, Richardson, Harry, Alnahlawi, Mahmoud, Yew, Christopher, Ponnapalli, Priya, Tagliasacchi, Marco, Korchemniy, Alex, Kim, Yelin, Li, Dinghua, Rosgen, Bill, Levin, Kyle, Wiesner, Jeremy, Banzal, Praseem, Srinivasan, Praveen, Yu, Hongkun, Ünlü, Çağlar, Reid, David, Tung, Zora, Finchelstein, Daniel, Kumar, Ravin, Elisseeff, Andre, Huang, Jin, Zhang, Ming, Aguilar, Ricardo, Giménez, Mai, Xia, Jiawei, Dousse, Olivier, Gierke, Willi, Yates, Damion, Jalan, Komal, Li, Lu, Latorre-Chimoto, Eri, Nguyen, Duc Dung, Durden, Ken, Kallakuri, Praveen, Liu, Yaxin, Johnson, Matthew, Tsai, Tomy, Talbert, Alice, Liu, Jasmine, Neitz, Alexander, Elkind, Chen, Selvi, Marco, Jasarevic, Mimi, Soares, Livio Baldini, Cui, Albert, Wang, Pidong, Wang, Alek Wenjiao, Ye, Xinyu, Kallarackal, Krystal, Loher, Lucia, Lam, Hoi, Broder, Josef, Holtmann-Rice, Dan, Martin, Nina, Ramadhana, Bramandia, Shukla, Mrinal, Basu, Sujoy, Mohan, Abhi, Fernando, Nick, Fiedel, Noah, Paterson, Kim, Li, Hui, Garg, Ankush, Park, Jane, Choi, DongHyun, Wu, Diane, Singh, Sankalp, Zhang, Zhishuai, Globerson, Amir, Yu, Lily, Carpenter, John, Quitry, Félix de Chaumont, Radebaugh, Carey, Lin, Chu-Cheng, Tudor, Alex, Shroff, Prakash, Garmon, Drew, Du, Dayou, Vats, Neera, Lu, Han, Iqbal, Shariq, Yakubovich, Alex, Tripuraneni, Nilesh, Manyika, James, Qureshi, Haroon, Hua, Nan, Ngani, Christel, Raad, Maria Abi, Forbes, Hannah, Stanway, Jeff, Sundararajan, Mukund, Ungureanu, Victor, Bishop, Colton, Li, Yunjie, Venkatraman, Balaji, Li, Bo, Thornton, Chloe, Scellato, Salvatore, Gupta, Nishesh, Wang, Yicheng, Tenney, Ian, Wu, Xihui, Shenoy, Ashish, Carvajal, Gabriel, Wright, Diana Gage, Bariach, Ben, Xiao, Zhuyun, Hawkins, Peter, Dalmia, Sid, Farabet, Clement, Valenzuela, Pedro, Yuan, Quan, Agarwal, Ananth, Chen, Mia, Kim, Wooyeol, Hulse, Brice, Dukkipati, Nandita, Paszke, Adam, Bolt, Andrew, Choo, Kiam, Beattie, Jennifer, Prendki, Jennifer, Vashisht, Harsha, Santamaria-Fernandez, Rebeca, Cobo, Luis C., Wilkiewicz, Jarek, Madras, David, Elqursh, Ali, Uy, Grant, Ramirez, Kevin, Harvey, Matt, Liechty, Tyler, Zen, Heiga, Seibert, Jeff, Hu, Clara Huiyi, Khorlin, Andrey, Le, Maigo, Aharoni, Asaf, Li, Megan, Wang, Lily, Kumar, Sandeep, Casagrande, Norman, Hoover, Jay, Badawy, Dalia El, Soergel, David, Vnukov, Denis, Miecnikowski, Matt, Simsa, Jiri, Kumar, Praveen, Sellam, Thibault, Vlasic, Daniel, Daruki, Samira, Shabat, Nir, Zhang, John, Su, Guolong, Zhang, Jiageng, Liu, Jeremiah, Sun, Yi, Palmer, Evan, Ghaffarkhah, Alireza, Xiong, Xi, Cotruta, Victor, Fink, Michael, Dixon, Lucas, Sreevatsa, Ashwin, Goedeckemeyer, Adrian, Dimitriev, Alek, Jafari, Mohsen, Crocker, Remi, FitzGerald, Nicholas, Kumar, Aviral, Ghemawat, Sanjay, Philips, Ivan, Liu, Frederick, Liang, Yannie, Sterneck, Rachel, Repina, Alena, Wu, Marcus, Knight, Laura, Georgiev, Marin, Lee, Hyo, Askham, Harry, Chakladar, Abhishek, Louis, Annie, Crous, Carl, Cate, Hardie, Petrova, Dessie, Quinn, Michael, Owusu-Afriyie, Denese, Singhal, Achintya, Wei, Nan, Kim, Solomon, Vincent, Damien, Nasr, Milad, Choquette-Choo, Christopher A., Tojo, Reiko, Lu, Shawn, Casas, Diego de Las, Cheng, Yuchung, Bolukbasi, Tolga, Lee, Katherine, Fatehi, Saaber, Ananthanarayanan, Rajagopal, Patel, Miteyan, Kaed, Charbel, Li, Jing, Belle, Shreyas Rammohan, Chen, Zhe, Konzelmann, Jaclyn, Põder, Siim, Garg, Roopal, Koverkathu, Vinod, Brown, Adam, Dyer, Chris, Liu, Rosanne, Nova, Azade, Xu, Jun, Walton, Alanna, Parrish, Alicia, Epstein, Mark, McCarthy, Sara, Petrov, Slav, Hassabis, Demis, Kavukcuoglu, Koray, Dean, Jeffrey, and Vinyals, Oriol
Abstract: In this report, we present the latest model of the Gemini family, Gemini 1.5 Pro, a highly compute-efficient multimodal mixture-of-experts model capable of recalling and reasoning over fine-grained information from millions of tokens of context, including multiple long documents and hours of video and audio. Gemini 1.5 Pro achieves near-perfect recall on long-context retrieval tasks across modalities, improves the state-of-the-art in long-document QA, long-video QA and long-context ASR, and matches or surpasses Gemini 1.0 Ultra's state-of-the-art performance across a broad set of benchmarks. Studying the limits of Gemini 1.5 Pro's long-context ability, we find continued improvement in next-token prediction and near-perfect retrieval (>99%) up to at least 10M tokens, a generational leap over existing models such as Claude 2.1 (200k) and GPT-4 Turbo (128k). Finally, we highlight surprising new capabilities of large language models at the frontier; when given a grammar manual for Kalamang, a language with fewer than 200 speakers worldwide, the model learns to translate English to Kalamang at a similar level to a person who learned from the same content.
Published: 2024

9. Precision and Adaptability of YOLOv5 and YOLOv8 in Dynamic Robotic Environments

Author: Kich, Victor A., Muttaqien, Muhammad A., Toyama, Junya, Miyoshi, Ryutaro, Ida, Yosuke, Ohya, Akihisa, Date, Hisashi, Kich, Victor A., Muttaqien, Muhammad A., Toyama, Junya, Miyoshi, Ryutaro, Ida, Yosuke, Ohya, Akihisa, and Date, Hisashi
Abstract: Recent advancements in real-time object detection frameworks have spurred extensive research into their application in robotic systems. This study provides a comparative analysis of YOLOv5 and YOLOv8 models, challenging the prevailing assumption of the latter's superiority in performance metrics. Contrary to initial expectations, YOLOv5 models demonstrated comparable, and in some cases superior, precision in object detection tasks. Our analysis delves into the underlying factors contributing to these findings, examining aspects such as model architecture complexity, training dataset variances, and real-world applicability. Through rigorous testing and an ablation study, we present a nuanced understanding of each model's capabilities, offering insights into the selection and optimization of object detection frameworks for robotic applications. Implications of this research extend to the design of more efficient and contextually adaptive systems, emphasizing the necessity for a holistic approach to evaluating model performance., Comment: 11th IEEE International Conference on Cybernetics and Intelligent Systems (CIS)
Published: 2024

10. AndroidWorld: A Dynamic Benchmarking Environment for Autonomous Agents

Author: Rawles, Christopher, Clinckemaillie, Sarah, Chang, Yifan, Waltz, Jonathan, Lau, Gabrielle, Fair, Marybeth, Li, Alice, Bishop, William, Li, Wei, Campbell-Ajala, Folawiyo, Toyama, Daniel, Berry, Robert, Tyamagundlu, Divya, Lillicrap, Timothy, Riva, Oriana, Rawles, Christopher, Clinckemaillie, Sarah, Chang, Yifan, Waltz, Jonathan, Lau, Gabrielle, Fair, Marybeth, Li, Alice, Bishop, William, Li, Wei, Campbell-Ajala, Folawiyo, Toyama, Daniel, Berry, Robert, Tyamagundlu, Divya, Lillicrap, Timothy, and Riva, Oriana
Abstract: Autonomous agents that execute human tasks by controlling computers can enhance human productivity and application accessibility. Yet, progress in this field will be driven by realistic and reproducible benchmarks. We present AndroidWorld, a fully functioning Android environment that provides reward signals for 116 programmatic task workflows across 20 real world Android applications. Unlike existing interactive environments, which provide a static test set, AndroidWorld dynamically constructs tasks that are parameterized and expressed in natural language in unlimited ways, thus enabling testing on a much larger and realistic suite of tasks. Reward signals are derived from the computer's system state, making them durable across task variations and extensible across different apps. To demonstrate AndroidWorld's benefits and mode of operation, we introduce a new computer control agent, M3A. M3A can complete 30.6% of the AndroidWorld's tasks, leaving ample room for future work. Furthermore, we adapt a popular desktop web agent to work on Android, which we find to be less effective on mobile, suggesting future research is needed to achieve universal, cross-domain agents. Finally, we conduct a robustness analysis by testing M3A against a range of task variations on a representative subset of tasks, demonstrating that variations in task parameters can significantly alter the complexity of a task and therefore an agent's performance, highlighting the importance of testing agents under diverse conditions. AndroidWorld and the experiments in this paper are available at https://github.com/google-research/android_world.
Published: 2024

11. Electric Vehicle Routing Problem for Emergency Power Supply: Towards Telecom Base Station Relief

Author: Kikuta, Daisuke, Ikeuchi, Hiroki, Tajiri, Kengo, Toyama, Yuta, Nakamura, Masaki, Nakano, Yuusuke, Kikuta, Daisuke, Ikeuchi, Hiroki, Tajiri, Kengo, Toyama, Yuta, Nakamura, Masaki, and Nakano, Yuusuke
Abstract: As a telecom provider, our company has a critical mission to maintain telecom services even during power outages. To accomplish the mission, it is essential to maintain the power of the telecom base stations. Here we consider a solution where electric vehicles (EVs) directly supply power to base stations by traveling to their locations. The goal is to find EV routes that minimize both the total travel distance of all EVs and the number of downed base stations. In this paper, we formulate this routing problem as a new variant of the Electric Vehicle Routing Problem (EVRP) and propose a solver that combines a rule-based vehicle selector and a reinforcement learning (RL)-based node selector. The rule of the vehicle selector ensures the exact environmental states when the selected EV starts to move. In addition, the node selection by the RL model enables fast route generation, which is critical in emergencies. We evaluate our solver on both synthetic datasets and real datasets. The results show that our solver outperforms baselines in terms of the objective value and computation time. Moreover, we analyze the generalization and scalability of our solver, demonstrating the capability toward unseen settings and large-scale problems. Check also our project page: https://ntt-dkiku.github.io/rl-evrpeps., Comment: Accepted at AAMAS 2024 (extended abstract). 10 pages, 5 figures. Work in progress
Published: 2024

12. GATA6 coordinates cross-talk between BMP10 and oxidative stress axis in pulmonary arterial hypertension.

Author: Toyama, Tetsuo, Toyama, Tetsuo, Kudryashova, Tatiana V, Ichihara, Asako, Lenna, Stefania, Looney, Agnieszka, Shen, Yuanjun, Jiang, Lifeng, Teos, Leyla, Avolio, Theodore, Lin, Derek, Kaplan, Ulas, Marden, Grace, Dambal, Vrinda, Goncharov, Dmitry, Delisser, Horace, Lafyatis, Robert, Seta, Francesca, Goncharova, Elena A, Trojanowska, Maria, Toyama, Tetsuo, Toyama, Tetsuo, Kudryashova, Tatiana V, Ichihara, Asako, Lenna, Stefania, Looney, Agnieszka, Shen, Yuanjun, Jiang, Lifeng, Teos, Leyla, Avolio, Theodore, Lin, Derek, Kaplan, Ulas, Marden, Grace, Dambal, Vrinda, Goncharov, Dmitry, Delisser, Horace, Lafyatis, Robert, Seta, Francesca, Goncharova, Elena A, and Trojanowska, Maria
Abstract: Pulmonary arterial hypertension (PAH) is a life-threatening condition characterized by a progressive increase in pulmonary vascular resistance leading to right ventricular failure and often death. Here we report that deficiency of transcription factor GATA6 is a shared pathological feature of PA endothelial (PAEC) and smooth muscle cells (PASMC) in human PAH and experimental PH, which is responsible for maintenance of hyper-proliferative cellular phenotypes, pulmonary vascular remodeling and pulmonary hypertension. We further show that GATA6 acts as a transcription factor and direct positive regulator of anti-oxidant enzymes, and its deficiency in PAH/PH pulmonary vascular cells induces oxidative stress and mitochondrial dysfunction. We demonstrate that GATA6 is regulated by the BMP10/BMP receptors axis and its loss in PAECs and PASMC in PAH supports BMPR deficiency. In addition, we have established that GATA6-deficient PAEC, acting in a paracrine manner, increase proliferation and induce other pathological changes in PASMC, supporting the importance of GATA6 in pulmonary vascular cell communication. Treatment with dimethyl fumarate resolved oxidative stress and BMPR deficiency, reversed hemodynamic changes caused by endothelial Gata6 loss in mice, and inhibited proliferation and induced apoptosis in human PAH PASMC, strongly suggesting that targeting GATA6 deficiency may provide a therapeutic advance for patients with PAH.
Published: 2023

13. Predictors of enhancing human physical attractiveness: Data from 93 countries

Author: Kowal, M, Sorokowski, P, Pisanski, K, Valentova, J, Varella, M, Frederick, D, Al-Shawaf, L, García, F, Giammusso, I, Gjoneska, B, Kozma, L, Otterbring, T, Papadatou-Pastou, M, Pfuhl, G, Stöckli, S, Studzinska, A, Toplu-Demirtaş, E, Touloumakos, A, Bakos, B, Batres, C, Bonneterre, S, Czamanski-Cohen, J, Dacanay, J, Deschrijver, E, Fisher, M, Grano, C, Grigoryev, D, Kačmár, P, Kozlov, M, Manunta, E, Massar, K, Mcfall, J, Mebarak, M, Miccoli, M, Milfont, T, Prokop, P, Aavik, T, Arriaga, P, Baiocco, R, Čeněk, J, Çetinkaya, H, Duyar, I, Guemaz, F, Ishii, T, Kamburidis, J, Khun-Inkeeree, H, Lidborg, L, Manor, H, Nussinson, R, Omar-Fauzee, M, Pazhoohi, F, Ponnet, K, Santos, A, Senyk, O, Spasovski, O, Vintila, M, Wang, A, Yoo, G, Zerhouni, O, Amin, R, Aquino, S, Boğa, M, Boussena, M, Can, A, Can, S, Castro, R, Chirumbolo, A, Çoker, O, Cornec, C, Dural, S, Eder, S, Moharrampour, N, Grassini, S, Hristova, E, Ikizer, G, Kervyn, N, Koyuncu, M, Kunisato, Y, Lins, S, Mandzyk, T, Mari, S, Mattiassi, A, Memisoglu-Sanli, A, Morelli, M, Novaes, F, Parise, M, Banai, I, Perun, M, Plohl, N, Sahli, F, Šakan, D, Smojver-Azic, S, Solak, Ç, Söylemez, S, Toyama, A, Wlodarczyk, A, Yamada, Y, Abad-Villaverde, B, Afhami, R, Akello, G, Alami, N, Alma, L, Argyrides, M, Atamtürk, D, Burduli, N, Cardona, S, Carneiro, J, Castañeda, A, Chałatkiewicz, I, Chopik, W, Chubinidze, D, Conroy-Beam, D, Contreras-Garduño, J, da Silva, D, Don, Y, Donato, S, Dubrov, D, Duračková, M, Dutt, S, Ebimgbo, S, Estevan, I, Etchezahar, E, Fedor, P, Fekih-Romdhane, F, Frackowiak, T, Galasinska, K, Gargula, Ł, Gelbart, B, Yepes, T, Hamdaoui, B, Hromatko, I, Itibi, S, Jaforte, L, Janssen, S, Jovic, M, Kertechian, K, Khan, F, Kobylarek, A, Koso-Drljevic, M, Krasnodębska, A, Križanić, V, Landa-Blanco, M, Mailhos, A, Marot, T, Dorcic, T, Martinez-Banfi, M, Yusof, M, Mayorga-Lascano, M, Mikuličiūtė, V, Mišetić, K, Musil, B, Najmussaqib, A, Muthu, K, Natividade, J, Ndukaihe, I, Nyhus, E, Oberzaucher, E, Omar, S, Ostaszewski, F, Pacquing, M, Pagani, A, Park, J, Pirtskhalava, E, Reips, U, Reyes, M, Röer, J, Şahin, A, Samekin, A, Sargautytė, R, Semenovskikh, T, Siepelmeyer, H, Singh, S, Sołtys, A, Sorokowska, A, Soto-López, R, Sultanova, L, Tamayo-Agudelo, W, Tan, C, Topanova, G, Bulut, M, Trémolière, B, Tulyakul, S, Türkan, B, Urbanek, A, Volkodav, T, Walter, K, Yaakob, M, Zumárraga-Espinosa, M, Kowal, Marta, Sorokowski, Piotr, Pisanski, Katarzyna, Valentova, Jaroslava V., Varella, Marco A. C., Frederick, David A., Al-Shawaf, Laith, García, Felipe E., Giammusso, Isabella, Gjoneska, Biljana, Kozma, Luca, Otterbring, Tobias, Papadatou-Pastou, Marietta, Pfuhl, Gerit, Stöckli, Sabrina, Studzinska, Anna, Toplu-Demirtaş, Ezgi, Touloumakos, Anna K., Bakos, Bence E., Batres, Carlota, Bonneterre, Solenne, Czamanski-Cohen, Johanna, Dacanay, Jovi C., Deschrijver, Eliane, Fisher, Maryanne L., Grano, Caterina, Grigoryev, Dmitry, Kačmár, Pavol, Kozlov, Mikhail V., Manunta, Efisio, Massar, Karlijn, McFall, Joseph P., Mebarak, Moises, Miccoli, Maria Rosa, Milfont, Taciano L., Prokop, Pavol, Aavik, Toivo, Arriaga, Patrícia, Baiocco, Roberto, Čeněk, Jiří, Çetinkaya, Hakan, Duyar, Izzet, Guemaz, Farida, Ishii, Tatsunori, Kamburidis, Julia A., Khun-Inkeeree, Hareesol, Lidborg, Linda H., Manor, Hagar, Nussinson, Ravit, Omar-Fauzee, Mohd Sofian B., Pazhoohi, Farid, Ponnet, Koen, Santos, Anabela Caetano, Senyk, Oksana, Spasovski, Ognen, Vintila, Mona, Wang, Austin H., Yoo, Gyesook, Zerhouni, Oulmann, Amin, Rizwana, Aquino, Sibele, Boğa, Merve, Boussena, Mahmoud, Can, Ali R., Can, Seda, Castro, Rita, Chirumbolo, Antonio, Çoker, Ogeday, Cornec, Clément, Dural, Seda, Eder, Stephanie J., Moharrampour, Nasim Ghahraman, Grassini, Simone, Hristova, Evgeniya, Ikizer, Gözde, Kervyn, Nicolas, Koyuncu, Mehmet, Kunisato, Yoshihiko, Lins, Samuel, Mandzyk, Tetyana, Mari, Silvia, Mattiassi, Alan D. A., Memisoglu-Sanli, Aybegum, Morelli, Mara, Novaes, Felipe C., Parise, Miriam, Banai, Irena Pavela, Perun, Mariia, Plohl, Nejc, Sahli, Fatima Zahra, Šakan, Dušana, Smojver-Azic, Sanja, Solak, Çağlar, Söylemez, Sinem, Toyama, Asako, Wlodarczyk, Anna, Yamada, Yuki, Abad-Villaverde, Beatriz, Afhami, Reza, Akello, Grace, Alami, Nael H., Alma, Leyla, Argyrides, Marios, Atamtürk, Derya, Burduli, Nana, Cardona, Sayra, Carneiro, João, Castañeda, Andrea, Chałatkiewicz, Izabela, Chopik, William J., Chubinidze, Dimitri, Conroy-Beam, Daniel, Contreras-Garduño, Jorge, da Silva, Diana Ribeiro, Don, Yahya B., Donato, Silvia, Dubrov, Dmitrii, Duračková, Michaela, Dutt, Sanjana, Ebimgbo, Samuel O., Estevan, Ignacio, Etchezahar, Edgardo, Fedor, Peter, Fekih-Romdhane, Feten, Frackowiak, Tomasz, Galasinska, Katarzyna, Gargula, Łukasz, Gelbart, Benjamin, Yepes, Talia Gomez, Hamdaoui, Brahim, Hromatko, Ivana, Itibi, Salome N., Jaforte, Luna, Janssen, Steve M. J., Jovic, Marija, Kertechian, Kevin S., Khan, Farah, Kobylarek, Aleksander, Koso-Drljevic, Maida, Krasnodębska, Anna, Križanić, Valerija, Landa-Blanco, Miguel, Mailhos, Alvaro, Marot, Tiago, Dorcic, Tamara Martinac, Martinez-Banfi, Martha, Yusof, Mat Rahimi, Mayorga-Lascano, Marlon, Mikuličiūtė, Vita, Mišetić, Katarina, Musil, Bojan, Najmussaqib, Arooj, Muthu, Kavitha Nalla, Natividade, Jean C., Ndukaihe, Izuchukwu L. G., Nyhus, Ellen K., Oberzaucher, Elisabeth, Omar, Salma S., Ostaszewski, Franciszek, Pacquing, Ma. Criselda T., Pagani, Ariela F., Park, Ju Hee, Pirtskhalava, Ekaterine, Reips, Ulf-Dietrich, Reyes, Marc Eric S., Röer, Jan P., Şahin, Ayşegül, Samekin, Adil, Sargautytė, Rūta, Semenovskikh, Tatiana, Siepelmeyer, Henrik, Singh, Sangeeta, Sołtys, Alicja, Sorokowska, Agnieszka, Soto-López, Rodrigo, Sultanova, Liliya, Tamayo-Agudelo, William, Tan, Chee-Seng, Topanova, Gulmira T., Bulut, Merve Topcu, Trémolière, Bastien, Tulyakul, Singha, Türkan, Belgüzar N., Urbanek, Arkadiusz, Volkodav, Tatiana, Walter, Kathryn V., Yaakob, Mohd Faiz Mohd, Zumárraga-Espinosa, Marcos, Kowal, M, Sorokowski, P, Pisanski, K, Valentova, J, Varella, M, Frederick, D, Al-Shawaf, L, García, F, Giammusso, I, Gjoneska, B, Kozma, L, Otterbring, T, Papadatou-Pastou, M, Pfuhl, G, Stöckli, S, Studzinska, A, Toplu-Demirtaş, E, Touloumakos, A, Bakos, B, Batres, C, Bonneterre, S, Czamanski-Cohen, J, Dacanay, J, Deschrijver, E, Fisher, M, Grano, C, Grigoryev, D, Kačmár, P, Kozlov, M, Manunta, E, Massar, K, Mcfall, J, Mebarak, M, Miccoli, M, Milfont, T, Prokop, P, Aavik, T, Arriaga, P, Baiocco, R, Čeněk, J, Çetinkaya, H, Duyar, I, Guemaz, F, Ishii, T, Kamburidis, J, Khun-Inkeeree, H, Lidborg, L, Manor, H, Nussinson, R, Omar-Fauzee, M, Pazhoohi, F, Ponnet, K, Santos, A, Senyk, O, Spasovski, O, Vintila, M, Wang, A, Yoo, G, Zerhouni, O, Amin, R, Aquino, S, Boğa, M, Boussena, M, Can, A, Can, S, Castro, R, Chirumbolo, A, Çoker, O, Cornec, C, Dural, S, Eder, S, Moharrampour, N, Grassini, S, Hristova, E, Ikizer, G, Kervyn, N, Koyuncu, M, Kunisato, Y, Lins, S, Mandzyk, T, Mari, S, Mattiassi, A, Memisoglu-Sanli, A, Morelli, M, Novaes, F, Parise, M, Banai, I, Perun, M, Plohl, N, Sahli, F, Šakan, D, Smojver-Azic, S, Solak, Ç, Söylemez, S, Toyama, A, Wlodarczyk, A, Yamada, Y, Abad-Villaverde, B, Afhami, R, Akello, G, Alami, N, Alma, L, Argyrides, M, Atamtürk, D, Burduli, N, Cardona, S, Carneiro, J, Castañeda, A, Chałatkiewicz, I, Chopik, W, Chubinidze, D, Conroy-Beam, D, Contreras-Garduño, J, da Silva, D, Don, Y, Donato, S, Dubrov, D, Duračková, M, Dutt, S, Ebimgbo, S, Estevan, I, Etchezahar, E, Fedor, P, Fekih-Romdhane, F, Frackowiak, T, Galasinska, K, Gargula, Ł, Gelbart, B, Yepes, T, Hamdaoui, B, Hromatko, I, Itibi, S, Jaforte, L, Janssen, S, Jovic, M, Kertechian, K, Khan, F, Kobylarek, A, Koso-Drljevic, M, Krasnodębska, A, Križanić, V, Landa-Blanco, M, Mailhos, A, Marot, T, Dorcic, T, Martinez-Banfi, M, Yusof, M, Mayorga-Lascano, M, Mikuličiūtė, V, Mišetić, K, Musil, B, Najmussaqib, A, Muthu, K, Natividade, J, Ndukaihe, I, Nyhus, E, Oberzaucher, E, Omar, S, Ostaszewski, F, Pacquing, M, Pagani, A, Park, J, Pirtskhalava, E, Reips, U, Reyes, M, Röer, J, Şahin, A, Samekin, A, Sargautytė, R, Semenovskikh, T, Siepelmeyer, H, Singh, S, Sołtys, A, Sorokowska, A, Soto-López, R, Sultanova, L, Tamayo-Agudelo, W, Tan, C, Topanova, G, Bulut, M, Trémolière, B, Tulyakul, S, Türkan, B, Urbanek, A, Volkodav, T, Walter, K, Yaakob, M, Zumárraga-Espinosa, M, Kowal, Marta, Sorokowski, Piotr, Pisanski, Katarzyna, Valentova, Jaroslava V., Varella, Marco A. C., Frederick, David A., Al-Shawaf, Laith, García, Felipe E., Giammusso, Isabella, Gjoneska, Biljana, Kozma, Luca, Otterbring, Tobias, Papadatou-Pastou, Marietta, Pfuhl, Gerit, Stöckli, Sabrina, Studzinska, Anna, Toplu-Demirtaş, Ezgi, Touloumakos, Anna K., Bakos, Bence E., Batres, Carlota, Bonneterre, Solenne, Czamanski-Cohen, Johanna, Dacanay, Jovi C., Deschrijver, Eliane, Fisher, Maryanne L., Grano, Caterina, Grigoryev, Dmitry, Kačmár, Pavol, Kozlov, Mikhail V., Manunta, Efisio, Massar, Karlijn, McFall, Joseph P., Mebarak, Moises, Miccoli, Maria Rosa, Milfont, Taciano L., Prokop, Pavol, Aavik, Toivo, Arriaga, Patrícia, Baiocco, Roberto, Čeněk, Jiří, Çetinkaya, Hakan, Duyar, Izzet, Guemaz, Farida, Ishii, Tatsunori, Kamburidis, Julia A., Khun-Inkeeree, Hareesol, Lidborg, Linda H., Manor, Hagar, Nussinson, Ravit, Omar-Fauzee, Mohd Sofian B., Pazhoohi, Farid, Ponnet, Koen, Santos, Anabela Caetano, Senyk, Oksana, Spasovski, Ognen, Vintila, Mona, Wang, Austin H., Yoo, Gyesook, Zerhouni, Oulmann, Amin, Rizwana, Aquino, Sibele, Boğa, Merve, Boussena, Mahmoud, Can, Ali R., Can, Seda, Castro, Rita, Chirumbolo, Antonio, Çoker, Ogeday, Cornec, Clément, Dural, Seda, Eder, Stephanie J., Moharrampour, Nasim Ghahraman, Grassini, Simone, Hristova, Evgeniya, Ikizer, Gözde, Kervyn, Nicolas, Koyuncu, Mehmet, Kunisato, Yoshihiko, Lins, Samuel, Mandzyk, Tetyana, Mari, Silvia, Mattiassi, Alan D. A., Memisoglu-Sanli, Aybegum, Morelli, Mara, Novaes, Felipe C., Parise, Miriam, Banai, Irena Pavela, Perun, Mariia, Plohl, Nejc, Sahli, Fatima Zahra, Šakan, Dušana, Smojver-Azic, Sanja, Solak, Çağlar, Söylemez, Sinem, Toyama, Asako, Wlodarczyk, Anna, Yamada, Yuki, Abad-Villaverde, Beatriz, Afhami, Reza, Akello, Grace, Alami, Nael H., Alma, Leyla, Argyrides, Marios, Atamtürk, Derya, Burduli, Nana, Cardona, Sayra, Carneiro, João, Castañeda, Andrea, Chałatkiewicz, Izabela, Chopik, William J., Chubinidze, Dimitri, Conroy-Beam, Daniel, Contreras-Garduño, Jorge, da Silva, Diana Ribeiro, Don, Yahya B., Donato, Silvia, Dubrov, Dmitrii, Duračková, Michaela, Dutt, Sanjana, Ebimgbo, Samuel O., Estevan, Ignacio, Etchezahar, Edgardo, Fedor, Peter, Fekih-Romdhane, Feten, Frackowiak, Tomasz, Galasinska, Katarzyna, Gargula, Łukasz, Gelbart, Benjamin, Yepes, Talia Gomez, Hamdaoui, Brahim, Hromatko, Ivana, Itibi, Salome N., Jaforte, Luna, Janssen, Steve M. J., Jovic, Marija, Kertechian, Kevin S., Khan, Farah, Kobylarek, Aleksander, Koso-Drljevic, Maida, Krasnodębska, Anna, Križanić, Valerija, Landa-Blanco, Miguel, Mailhos, Alvaro, Marot, Tiago, Dorcic, Tamara Martinac, Martinez-Banfi, Martha, Yusof, Mat Rahimi, Mayorga-Lascano, Marlon, Mikuličiūtė, Vita, Mišetić, Katarina, Musil, Bojan, Najmussaqib, Arooj, Muthu, Kavitha Nalla, Natividade, Jean C., Ndukaihe, Izuchukwu L. G., Nyhus, Ellen K., Oberzaucher, Elisabeth, Omar, Salma S., Ostaszewski, Franciszek, Pacquing, Ma. Criselda T., Pagani, Ariela F., Park, Ju Hee, Pirtskhalava, Ekaterine, Reips, Ulf-Dietrich, Reyes, Marc Eric S., Röer, Jan P., Şahin, Ayşegül, Samekin, Adil, Sargautytė, Rūta, Semenovskikh, Tatiana, Siepelmeyer, Henrik, Singh, Sangeeta, Sołtys, Alicja, Sorokowska, Agnieszka, Soto-López, Rodrigo, Sultanova, Liliya, Tamayo-Agudelo, William, Tan, Chee-Seng, Topanova, Gulmira T., Bulut, Merve Topcu, Trémolière, Bastien, Tulyakul, Singha, Türkan, Belgüzar N., Urbanek, Arkadiusz, Volkodav, Tatiana, Walter, Kathryn V., Yaakob, Mohd Faiz Mohd, and Zumárraga-Espinosa, Marcos
Abstract: People across the world and throughout history have gone to great lengths to enhance their physical appearance. Evolutionary psychologists and ethologists have largely attempted to explain this phenomenon via mating preferences and strategies. Here, we test one of the most popular evolutionary hypotheses for beauty-enhancing behaviors, drawn from mating market and parasite stress perspectives, in a large cross-cultural sample. We also test hypotheses drawn from other influential and non-mutually exclusive theoretical frameworks, from biosocial role theory to a cultural media perspective. Survey data from 93,158 human participants across 93 countries provide evidence that behaviors such as applying makeup or using other cosmetics, hair grooming, clothing style, caring for body hygiene, and exercising or following a specific diet for the specific purpose of improving ones physical attractiveness, are universal. Indeed, 99% of participants reported spending >10 min a day performing beauty-enhancing behaviors. The results largely support evolutionary hypotheses: more time was spent enhancing beauty by women (almost 4 h a day, on average) than by men (3.6 h a day), by the youngest participants (and contrary to predictions, also the oldest), by those with a relatively more severe history of infectious diseases, and by participants currently dating compared to those in established relationships. The strongest predictor of attractiveness-enhancing behaviors was social media usage. Other predictors, in order of effect size, included adhering to traditional gender roles, residing in countries with less gender equality, considering oneself as highly attractive or, conversely, highly unattractive, TV watching time, higher socioeconomic status, right-wing political beliefs, a lower level of education, and personal individualistic attitudes. This study provides novel insight into universal beauty-enhancing behaviors by unifying evolutionary theory with several other complement
Published: 2022

14. Seasonal Variability of the Surface Ocean Carbon Cycle: A Synthesis

Author: Rodgers, Keith B, Schwinger, Jörg, Fassbender, Andrea J, Landschützer, Peter, Yamaguchi, Ryohei, Frenzel, Hartmut, Stein, Karl, Müller, Jens Daniel, Goris, Nadine, Sharma, Sahil, Bushinsky, Seth, Chau, Thi‐Tuyet‐Trang, Gehlen, Marion, Gallego, M Angeles, Gloege, Lucas, Gregor, Luke, Gruber, Nicolas, Hauck, Judith, Iida, Yosuke, Ishii, Masao, Keppler, Lydia, Kim, Ji‐Eun, Schlunegger, Sarah, Tjiputra, Jerry, Toyama, Katsuya, Ayar, Pradeebane Vaittinada, Velo, Antón, Rodgers, Keith B, Schwinger, Jörg, Fassbender, Andrea J, Landschützer, Peter, Yamaguchi, Ryohei, Frenzel, Hartmut, Stein, Karl, Müller, Jens Daniel, Goris, Nadine, Sharma, Sahil, Bushinsky, Seth, Chau, Thi‐Tuyet‐Trang, Gehlen, Marion, Gallego, M Angeles, Gloege, Lucas, Gregor, Luke, Gruber, Nicolas, Hauck, Judith, Iida, Yosuke, Ishii, Masao, Keppler, Lydia, Kim, Ji‐Eun, Schlunegger, Sarah, Tjiputra, Jerry, Toyama, Katsuya, Ayar, Pradeebane Vaittinada, and Velo, Antón
Abstract: The seasonal cycle is the dominant mode of variability in the air-sea CO2 flux in most regions of the global ocean, yet discrepancies between different seasonality estimates are rather large. As part of the Regional Carbon Cycle Assessment and Processes Phase 2 project (RECCAP2), we synthesize surface ocean pCO2 and air-sea CO2 flux seasonality from models and observation-based estimates, focusing on both a present-day climatology and decadal changes between the 1980s and 2010s. Four main findings emerge: First, global ocean biogeochemistry models (GOBMs) and observation-based estimates (pCO2 products) of surface pCO2 seasonality disagree in amplitude and phase, primarily due to discrepancies in the seasonal variability in surface DIC. Second, the seasonal cycle in pCO2 has increased in amplitude over the last three decades in both pCO2 products and GOBMs. Third, decadal increases in pCO2 seasonal cycle amplitudes in subtropical biomes for both pCO2 products and GOBMs are driven by increasing DIC concentrations stemming from the uptake of anthropogenic CO2 (Cant). In subpolar and Southern Ocean biomes, however, the seasonality change for GOBMs is dominated by Cant invasion, whereas for pCO2 products an indeterminate combination of Cant invasion and climate change modulates the changes. Fourth, biome-aggregated decadal changes in the amplitude of pCO2 seasonal variability are largely detectable against both mapping uncertainty (reducible) and natural variability uncertainty (irreducible), but not at the gridpoint scale over much of the northern subpolar oceans and over the Southern Ocean, underscoring the importance of sustained high-quality seasonally resolved measurements over these regions.
Published: 2023

15. Modeling Low Muscle Mass Screening in Hemodialysis Patients

Author: Senzaki, Daiki, Yoshioka, Nobuo, Nagakawa, Osamu, Inayama, Emi, Nakagawa, Takafumi, Takayama, Hidehito, Endo, Toko, Nakajima, Fumitaka, Fukui, Masayoshi, Kijima, Yasuaki, Oyama, Yasuo, Kudo, Risshi, Toyama, Tadashi, Yamada, Yosuke, Tsurusaki, Kiyoshi, Aoyama, Naoki, Matsumura, Takayasu, Yamahara, Hideki, Miyasato, Kenro, Kitamura, Tetsuya, Ikenoue, Tatsuyoshi, Senzaki, Daiki, Yoshioka, Nobuo, Nagakawa, Osamu, Inayama, Emi, Nakagawa, Takafumi, Takayama, Hidehito, Endo, Toko, Nakajima, Fumitaka, Fukui, Masayoshi, Kijima, Yasuaki, Oyama, Yasuo, Kudo, Risshi, Toyama, Tadashi, Yamada, Yosuke, Tsurusaki, Kiyoshi, Aoyama, Naoki, Matsumura, Takayasu, Yamahara, Hideki, Miyasato, Kenro, Kitamura, Tetsuya, and Ikenoue, Tatsuyoshi
Abstract: Introduction: Computed tomography (CT) can accurately measure muscle mass, which is necessary for diagnosing sarcopenia, even in dialysis patients. However, CT-based screening for such patients is challenging, especially considering the availability of equipment within dialysis facilities. We therefore aimed to develop a bedside prediction model for low muscle mass, defined by the psoas muscle mass index (PMI) from CT measurement. Methods: Hemodialysis patients (n = 619) who had undergone abdominal CT screening were divided into the development (n = 441) and validation (n = 178) groups. PMI was manually measured using abdominal CT images to diagnose low muscle mass by two independent investigators. The development group’s data were used to create a logistic regression model using 42 items extracted from clinical information as predictive variables; variables were selected using the stepwise method. External validity was examined using the validation group’s data, and the area under the curve (AUC), sensitivity, and specificity were calculated. Results: Of all subjects, 226 (37%) were diagnosed with low muscle mass using PMI. A predictive model for low muscle mass was calculated using ten variables: each grip strength, sex, height, dry weight, primary cause of end-stage renal disease, diastolic blood pressure at start of session, pre-dialysis potassium and albumin level, and dialysis water removal in a session. The development group’s adjusted AUC, sensitivity, and specificity were 0.81, 60%, and 87%, respectively. The validation group’s adjusted AUC, sensitivity, and specificity were 0.73, 64%, and 82%, respectively. Discussion/Conclusion: Our results facilitate skeletal muscle screening in hemodialysis patients, assisting in sarcopenia prophylaxis and intervention decisions.
Published: 2023

16. Integrated genetic and clinical prognostic factors for aggressive adult T-cell leukemia/lymphoma

Author: 70866582, Kameda, Takuro, Kataoka, Keisuke, Kamiunten, Ayako, Hidaka, Michihiro, Miyoshi, Hiroaki, Nakano, Nobuaki, Nosaka, Kisato, Yoshimitsu, Makoto, Yasunaga, Jun-Ichirou, Kogure, Yasunori, Shide, Kotaro, Miyahara, Masaharu, Sakamoto, Takashi, Akizuki, Keiichi, Hidaka, Tomonori, Kubuki, Yoko, Koya, Junji, Kawano, Noriaki, Yamashita, Kiyoshi, Kawano, Hiroshi, Toyama, Takanori, Maeda, Kouichi, Marutsuka, Kosuke, Imaizumi, Yoshitaka, Kato, Koji, Sugio, Takeshi, Tokunaga, Masahito, Tashiro, Yukie, Takaori-Kondo, Akifumi, Miyazaki, Yasushi, Akashi, Koichi, Ishitsuka, Kenji, Matsuoka, Masao, Ohshima, Koichi, Watanabe, Toshiki, Kitanaka, Akira, Utsunomiya, Atae, Ogawa, Seishi, Shimoda, Kazuya, 70866582, Kameda, Takuro, Kataoka, Keisuke, Kamiunten, Ayako, Hidaka, Michihiro, Miyoshi, Hiroaki, Nakano, Nobuaki, Nosaka, Kisato, Yoshimitsu, Makoto, Yasunaga, Jun-Ichirou, Kogure, Yasunori, Shide, Kotaro, Miyahara, Masaharu, Sakamoto, Takashi, Akizuki, Keiichi, Hidaka, Tomonori, Kubuki, Yoko, Koya, Junji, Kawano, Noriaki, Yamashita, Kiyoshi, Kawano, Hiroshi, Toyama, Takanori, Maeda, Kouichi, Marutsuka, Kosuke, Imaizumi, Yoshitaka, Kato, Koji, Sugio, Takeshi, Tokunaga, Masahito, Tashiro, Yukie, Takaori-Kondo, Akifumi, Miyazaki, Yasushi, Akashi, Koichi, Ishitsuka, Kenji, Matsuoka, Masao, Ohshima, Koichi, Watanabe, Toshiki, Kitanaka, Akira, Utsunomiya, Atae, Ogawa, Seishi, and Shimoda, Kazuya
Abstract: The prognosis of aggressive adult T-cell leukemia/lymphoma (ATL) is poor, and allogeneic hematopoietic stem-cell transplantation (allo-HSCT) is a curative treatment. To identify favorable prognostic patients after intensive chemotherapy, and who therefore might not require upfront allo-HSCT, we aimed to improve risk stratification of aggressive ATL patients aged <70 years. The clinical risk factors and genetic mutations were incorporated into risk modeling for overall survival (OS). We generated the m7-ATLPI, a clinicogenetic risk model for OS, that included the ATL prognostic index (PI) (ATL-PI) risk category, and non-silent mutations in seven genes, namely TP53, IRF4, RHOA, PRKCB, CARD11, CCR7, and GATA3. In the training cohort of 99 patients, the m7-ATLPI identified a low-, intermediate-, and high-risk group with 2-year OS of 100%, 43%, and 19%, respectively (hazard ratio [HR] 5.46, p < 0.0001). The m7-ATLPI achieved superior risk stratification compared to the current ATL-PI (C-index 0.92 vs. 0.85, respectively). In the validation cohort of 84 patients, the m7-ATLPI defined low-, intermediate-, and high-risk groups with a 2-year OS of 81%, 30%, and 0%, respectively (HR 2.33, p = 0.0094), and the model again outperformed the ATL-PI (C-index 0.72 vs. 0.70, respectively). The simplified m7-ATLPI, which is easier to use in clinical practice, achieved superior risk stratification compared to the ATL-PI, as did the original m7-ATLPI; the simplified version was calculated by summing the following: high-risk ATL-PI category (+10), low-risk ATL-PI category (−4), and non-silent mutations in TP53 (+4), IRF4 (+3), RHOA (+1), PRKCB (+1), CARD11 (+0.5), CCR7 (−2), and GATA3 (−3).
Published: 2023

17. A Bayesian estimation method for cerebral blood flow measurement by area-detector CT perfusion imaging.

Author: Murayama, K., Smit, E.J., Prokop, M., Ikeda, Y., Fujii, K., Nakahara, I., Hanamatsu, S., Katada, K., Ohno, Y., Toyama, H., Murayama, K., Smit, E.J., Prokop, M., Ikeda, Y., Fujii, K., Nakahara, I., Hanamatsu, S., Katada, K., Ohno, Y., and Toyama, H.
Abstract: 01 januari 2023, Item does not contain fulltext, PURPOSE: Bayesian estimation with advanced noise reduction (BEANR) in CT perfusion (CTP) could deliver more reliable cerebral blood flow (CBF) measurements than the commonly used reformulated singular value decomposition (rSVD). We compared the efficacy of CBF measurement by CTP using BEANR and rSVD, evaluating both relative to N-isopropyl-p-[(123) I]- iodoamphetamine ((123)I-IMP) single-photon emission computed tomography (SPECT) as a reference standard, in patients with cerebrovascular disease. METHODS: Thirty-one patients with suspected cerebrovascular disease underwent both CTP on a 320 detector-row CT system and SPECT. We applied rSVD and BEANR in the ischemic and contralateral regions to create CBF maps and calculate CBF ratios from the ischemic side to the healthy contralateral side (CBF index). The analysis involved comparing the CBF index between CTP methods and SPECT using Pearson's correlation and limits of agreement determined with Bland-Altman analyses, before comparing the mean difference in the CBF index between each CTP method and SPECT using the Wilcoxon matched pairs signed-rank test. RESULTS: The CBF indices of BEANR and (123)I-IMP SPECT were significantly and positively correlated (r = 0.55, p < 0.0001), but there was no significant correlation between the rSVD method and SPECT (r = 0.15, p > 0.05). BEANR produced smaller limits of agreement for CBF than rSVD. The mean difference in the CBF index between BEANR and SPECT differed significantly from that between rSVD and SPECT (p < 0.001). CONCLUSIONS: BEANR has a better potential utility for CBF measurement in CTP than rSVD compared to SPECT in patients with cerebrovascular disease.
Published: 2023

18. A Bayesian estimation method for cerebral blood flow measurement by area-detector CT perfusion imaging.

Author: Murayama, K., Smit, E.J., Prokop, M., Ikeda, Y., Fujii, K., Nakahara, I., Hanamatsu, S., Katada, K., Ohno, Y., Toyama, H., Murayama, K., Smit, E.J., Prokop, M., Ikeda, Y., Fujii, K., Nakahara, I., Hanamatsu, S., Katada, K., Ohno, Y., and Toyama, H.
Abstract: 01 januari 2023, Item does not contain fulltext, PURPOSE: Bayesian estimation with advanced noise reduction (BEANR) in CT perfusion (CTP) could deliver more reliable cerebral blood flow (CBF) measurements than the commonly used reformulated singular value decomposition (rSVD). We compared the efficacy of CBF measurement by CTP using BEANR and rSVD, evaluating both relative to N-isopropyl-p-[(123) I]- iodoamphetamine ((123)I-IMP) single-photon emission computed tomography (SPECT) as a reference standard, in patients with cerebrovascular disease. METHODS: Thirty-one patients with suspected cerebrovascular disease underwent both CTP on a 320 detector-row CT system and SPECT. We applied rSVD and BEANR in the ischemic and contralateral regions to create CBF maps and calculate CBF ratios from the ischemic side to the healthy contralateral side (CBF index). The analysis involved comparing the CBF index between CTP methods and SPECT using Pearson's correlation and limits of agreement determined with Bland-Altman analyses, before comparing the mean difference in the CBF index between each CTP method and SPECT using the Wilcoxon matched pairs signed-rank test. RESULTS: The CBF indices of BEANR and (123)I-IMP SPECT were significantly and positively correlated (r = 0.55, p < 0.0001), but there was no significant correlation between the rSVD method and SPECT (r = 0.15, p > 0.05). BEANR produced smaller limits of agreement for CBF than rSVD. The mean difference in the CBF index between BEANR and SPECT differed significantly from that between rSVD and SPECT (p < 0.001). CONCLUSIONS: BEANR has a better potential utility for CBF measurement in CTP than rSVD compared to SPECT in patients with cerebrovascular disease.
Published: 2023

19. Lamb wave mode conversion and multiple-reflection mechanisms for simply and reliably evaluating delamination in composite laminates

Author: Ryuzono, Kazuki, Yashiro, Shigeki, Onodera, Sota, Toyama, Nobuyuki, Ryuzono, Kazuki, Yashiro, Shigeki, Onodera, Sota, and Toyama, Nobuyuki
Abstract: type:Research Article, Lamb wave propagation must be understood comprehensively for simply evaluating delamination during ultrasonic testing. However, the difference between wave propagation, visualized using laser Doppler vibrometer and pulsed-laser scanners, has not been sufficiently investigated, and knowledge of optimal conditions for evaluating delamination is limited. Thus, in this study, the mode conversion and multiple reflections of Lamb waves propagating in a delaminated cross-ply laminate were visualized using different laser scanners, delamination depths, and wave incident angles. Delamination was characterized using maximum-amplitude map postprocessing under specific conditions. Further numerical analysis revealed that owing to multiple reflections of the antisymmetric mode in incident and mode-converted waves, standing waves were generated in the delaminated sublaminate. Dispersion curve and flexural stiffness calculations confirmed the conditions required for high-amplitude standing waves, thereby providing guidelines for simply and reliably evaluating delamination during inspections.
Published: 2023

20. Examination of postmortem changes in the lungs, trachea, and bronchi in a rat model imaged with small-animal computed tomography

Author: Matsuyama, Takahiro, Ota, Seiichiro, Inui, Yoshitaka, Fujii, Naoko, Tsukamoto, Tetsuya, Isobe, Ichiro, Tsujioka, Katsumi, Nagao, Shizuko, Tanabe, Ryosuke, Toyama, Hiroshi, Matsuyama, Takahiro, Ota, Seiichiro, Inui, Yoshitaka, Fujii, Naoko, Tsukamoto, Tetsuya, Isobe, Ichiro, Tsujioka, Katsumi, Nagao, Shizuko, Tanabe, Ryosuke, and Toyama, Hiroshi
Published: 2023

21. Adaptive Deadbeat Feedforward Compensation for Robust Positioning Performance Against Plant Perturbations

Author: Souichi, Toyama, Yousuke, Okado, 1000070769869, Yoshihiro, Maeda, 1000010232662, Makoto, Iwasaki, Hiromu, Hirai, Souichi, Toyama, Yousuke, Okado, 1000070769869, Yoshihiro, Maeda, 1000010232662, Makoto, Iwasaki, and Hiromu, Hirai
Abstract: Vicenza, Italy, 27 February - 1 March 2013
Published: 2023

22. Nutrients Associated with Sleep Bruxism

Author: Toyama, Naoki, Ekuni, Daisuke, Fukuhara, Daiki, Sawada, Nanami, Yamashita, Miho, Komiyama, Momoe, Nagahama, Takahiko, Morita, Manabu, Toyama, Naoki, Ekuni, Daisuke, Fukuhara, Daiki, Sawada, Nanami, Yamashita, Miho, Komiyama, Momoe, Nagahama, Takahiko, and Morita, Manabu
Abstract: Background: The purpose of the present research was to identify nutrients related to sleep bruxism and to establish a hypothesis regarding the relationship between sleep bruxism and nutrients. Methods: We recruited 143 Japanese university students in 2021 and assigned them to sleep bruxism (n = 58) and non-sleep bruxism groups (n = 85), using an identical single-channel wearable electromyography device. To investigate nutrient intakes, participants answered a food frequency questionnaire based on food groups. We assessed differences in nutrient intakes between the sleep bruxism and non-sleep bruxism groups. Results: Logistic regression modeling showed that sleep bruxism tended to be associated with dietary fiber (odds ratio, 0.91; 95% confidence interval, 0.83-1.00; p = 0.059). In addition, a subgroup analysis selecting students in the top and bottom quartiles of dietary fiber intake showed that students with sleep bruxism had a significantly lower dietary fiber intake (10.4 +/- 4.6 g) than those without sleep bruxism (13.4 +/- 6.1 g; p = 0.022). Conclusion: The present research showed that dietary fiber intake may be related to sleep bruxism. Therefore, we hypothesized that dietary fiber would improve sleep bruxism in young adults.
Published: 2023

23. Post-discharge clinical, laboratory and radiographic features of coronavirus disease 2019 (COVID-19) patients at university hospitals in Japan

Author: Sasaki, Toshiharu, Toyama, Yoko, Horiguchi, Tomoya, Hibino, Masaya, Tsuzuki, Sei-ichiro, Hayashi, Masamichi, Doi, Yohei, Iwata, Mitsunaga, Imaizumi, Kazuyoshi, Inaba, Masato, Sasaki, Toshiharu, Toyama, Yoko, Horiguchi, Tomoya, Hibino, Masaya, Tsuzuki, Sei-ichiro, Hayashi, Masamichi, Doi, Yohei, Iwata, Mitsunaga, Imaizumi, Kazuyoshi, and Inaba, Masato
Published: 2023

24. We Built it, But Did They Come: Veterans' Use of VA Healthcare System-Provided Complementary and Integrative Health Approaches.

Author: Taylor, Stephanie L, Taylor, Stephanie L, Gelman, Hannah M, DeFaccio, Rian, Douglas, Jamie, Hawrilenko, Matthew J, McGinty, Nathan K, Resnick, Adam, Tomlanovich, Nathan C, Toyama, Joy, Whitehead, Alison M, Kligler, Benjamin, Zeliadt, Steven B, Taylor, Stephanie L, Taylor, Stephanie L, Gelman, Hannah M, DeFaccio, Rian, Douglas, Jamie, Hawrilenko, Matthew J, McGinty, Nathan K, Resnick, Adam, Tomlanovich, Nathan C, Toyama, Joy, Whitehead, Alison M, Kligler, Benjamin, and Zeliadt, Steven B
Abstract: BackgroundInterest in complementary and integrative health (CIH) approaches, such as meditation, yoga, and acupuncture, continues to grow. The evidence of effectiveness for some CIH approaches has increased in the last decade, especially for pain, with many being recommended in varying degrees in national guidelines. To offer nonpharmacological health management options and meet patient demand, the nation's largest integrated healthcare system, the Veterans Health Administration (VA), greatly expanded their provision of CIH approaches recently.ObjectiveThis paper addressed the questions of how many VA patients might use CIH approaches and chiropractic care if they were available at modest to no fee, and would patients with some health conditions or characteristics be more likely than others to use these therapies.DesignUsing electronic medical records, we conducted a national, three-year, retrospective analysis of VA patients' use of eleven VA-covered therapies: chiropractic care, acupuncture, Battlefield Acupuncture, biofeedback, clinical hypnosis, guided imagery, massage therapy, meditation, Tai Chi/Qigong, and yoga.ParticipantsWe created a national cohort of veterans using VA healthcare from October 2016-September 2019.Key resultsVeterans' use of these approaches increased 70% in three years. By 2019, use was 5.7% among all VA patients, but highest among patients with chronic musculoskeletal pain (13.9%), post-traumatic stress disorder (PTSD; 10.6%), depression (10.4%), anxiety (10.2%), or obesity (7.8%). The approach used varied by age and race/ethnicity, with women being uniformly more likely than men to use each approach. Patients having chronic musculoskeletal pain, obesity, anxiety, depression, or PTSD were more likely than others to use each of the approaches.ConclusionsVeterans' use of some approaches rapidly grew recently and was robust, especially among patients most in need. This information might help shape federal/state health policy on the provision
Published: 2023

25. Histopathological findings affect quantitative values of single photon emission computed tomography in patients with antiresorptive agent-related osteonecrosis of the jaws

Author: Okui, Taro, Kobayashi, Yoshikazu, Isomura, Madoka, Tsujimoto, Masakazu, Satoh, Koji, Toyama, Hiroshi, Okui, Taro, Kobayashi, Yoshikazu, Isomura, Madoka, Tsujimoto, Masakazu, Satoh, Koji, and Toyama, Hiroshi
Published: 2023

26. Post-discharge clinical, laboratory and radiographic features of coronavirus disease 2019 (COVID-19) patients at university hospitals in Japan

Author: Sasaki, Toshiharu, Toyama, Yoko, Horiguchi, Tomoya, Hibino, Masaya, Tsuzuki, Sei-ichiro, Hayashi, Masamichi, Doi, Yohei, Iwata, Mitsunaga, Imaizumi, Kazuyoshi, Inaba, Masato, Sasaki, Toshiharu, Toyama, Yoko, Horiguchi, Tomoya, Hibino, Masaya, Tsuzuki, Sei-ichiro, Hayashi, Masamichi, Doi, Yohei, Iwata, Mitsunaga, Imaizumi, Kazuyoshi, and Inaba, Masato
Published: 2023

27. Lamb wave mode conversion and multiple-reflection mechanisms for simply and reliably evaluating delamination in composite laminates

Author: Ryuzono, Kazuki, Yashiro, Shigeki, Onodera, Sota, Toyama, Nobuyuki, Ryuzono, Kazuki, Yashiro, Shigeki, Onodera, Sota, and Toyama, Nobuyuki
Abstract: type:Research Article, Lamb wave propagation must be understood comprehensively for simply evaluating delamination during ultrasonic testing. However, the difference between wave propagation, visualized using laser Doppler vibrometer and pulsed-laser scanners, has not been sufficiently investigated, and knowledge of optimal conditions for evaluating delamination is limited. Thus, in this study, the mode conversion and multiple reflections of Lamb waves propagating in a delaminated cross-ply laminate were visualized using different laser scanners, delamination depths, and wave incident angles. Delamination was characterized using maximum-amplitude map postprocessing under specific conditions. Further numerical analysis revealed that owing to multiple reflections of the antisymmetric mode in incident and mode-converted waves, standing waves were generated in the delaminated sublaminate. Dispersion curve and flexural stiffness calculations confirmed the conditions required for high-amplitude standing waves, thereby providing guidelines for simply and reliably evaluating delamination during inspections.
Published: 2023

28. Examination of postmortem changes in the lungs, trachea, and bronchi in a rat model imaged with small-animal computed tomography

Author: Matsuyama, Takahiro, Ota, Seiichiro, Inui, Yoshitaka, Fujii, Naoko, Tsukamoto, Tetsuya, Isobe, Ichiro, Tsujioka, Katsumi, Nagao, Shizuko, Tanabe, Ryosuke, Toyama, Hiroshi, Matsuyama, Takahiro, Ota, Seiichiro, Inui, Yoshitaka, Fujii, Naoko, Tsukamoto, Tetsuya, Isobe, Ichiro, Tsujioka, Katsumi, Nagao, Shizuko, Tanabe, Ryosuke, and Toyama, Hiroshi
Published: 2023

29. Adaptive Deadbeat Feedforward Compensation for Robust Positioning Performance Against Plant Perturbations

Author: Souichi, Toyama, Yousuke, Okado, 1000070769869, Yoshihiro, Maeda, 1000010232662, Makoto, Iwasaki, Hiromu, Hirai, Souichi, Toyama, Yousuke, Okado, 1000070769869, Yoshihiro, Maeda, 1000010232662, Makoto, Iwasaki, and Hiromu, Hirai
Abstract: Vicenza, Italy, 27 February - 1 March 2013
Published: 2023

30. Nutrients Associated with Sleep Bruxism

Author: Toyama, Naoki, Ekuni, Daisuke, Fukuhara, Daiki, Sawada, Nanami, Yamashita, Miho, Komiyama, Momoe, Nagahama, Takahiko, Morita, Manabu, Toyama, Naoki, Ekuni, Daisuke, Fukuhara, Daiki, Sawada, Nanami, Yamashita, Miho, Komiyama, Momoe, Nagahama, Takahiko, and Morita, Manabu
Abstract: Background: The purpose of the present research was to identify nutrients related to sleep bruxism and to establish a hypothesis regarding the relationship between sleep bruxism and nutrients. Methods: We recruited 143 Japanese university students in 2021 and assigned them to sleep bruxism (n = 58) and non-sleep bruxism groups (n = 85), using an identical single-channel wearable electromyography device. To investigate nutrient intakes, participants answered a food frequency questionnaire based on food groups. We assessed differences in nutrient intakes between the sleep bruxism and non-sleep bruxism groups. Results: Logistic regression modeling showed that sleep bruxism tended to be associated with dietary fiber (odds ratio, 0.91; 95% confidence interval, 0.83-1.00; p = 0.059). In addition, a subgroup analysis selecting students in the top and bottom quartiles of dietary fiber intake showed that students with sleep bruxism had a significantly lower dietary fiber intake (10.4 +/- 4.6 g) than those without sleep bruxism (13.4 +/- 6.1 g; p = 0.022). Conclusion: The present research showed that dietary fiber intake may be related to sleep bruxism. Therefore, we hypothesized that dietary fiber would improve sleep bruxism in young adults.
Published: 2023

31. Histopathological findings affect quantitative values of single photon emission computed tomography in patients with antiresorptive agent-related osteonecrosis of the jaws

Author: Okui, Taro, Kobayashi, Yoshikazu, Isomura, Madoka, Tsujimoto, Masakazu, Satoh, Koji, Toyama, Hiroshi, Okui, Taro, Kobayashi, Yoshikazu, Isomura, Madoka, Tsujimoto, Masakazu, Satoh, Koji, and Toyama, Hiroshi
Published: 2023

32. The behavior of sympatric sea urchin species across an ecosystem state gradient

Author: Belleza, Dominic Franco C., Urae, Takeshi, Tanimae, Shin-ichiro, Toyama, Kento, Isoda, Akari, Nishihara, Gregory N., Belleza, Dominic Franco C., Urae, Takeshi, Tanimae, Shin-ichiro, Toyama, Kento, Isoda, Akari, and Nishihara, Gregory N.
Abstract: Background: In temperate macroalgal forests, sea urchins are considered as a keystone species due to their grazing ability. Given their potential to shape benthic communities, we monitored the habitat use by three sympatric sea urchin species and compared their behaviors in a vegetated habitat (VH) and an adjacent isoyake habitat (IH). Methods: We monitored the environmental conditions and sea urchin density along deep and shallow transects of the VH and IH for over a year. The benthic rugosity at both sites were also surveyed. A mark-recapture experiment was conducted on the two most abundant sea urchins, Diadema setosum and Heliocidaris crassispina, to elucidate sea urchin movement patterns and group dynamics. Results: We found that exposure to waves was highest at the VH while the IH was sheltered. The deep IH experienced the least amount of light due to high turbidity. Water temperature patterns were similar across sites. The VH benthic topography was more rugose compared to the smoother and silt-covered IH substate. Peak macroalgal bloom occurred three months earlier in IH, but macroalgae persisted longer at the shallow VH. Among the sympatric sea urchins, H. crassispina was most abundant at the shallow VH and was observed in pits and crevices. The most abundant across IH and in the deep VH was D. setosum, preferring either crevices or free-living, depending on hydrodynamic conditions. The least abundant species was D. savignyi, and most often observed in crevices. Small and medium sea urchins were most often observed at the IH site, whereas larger sea urchins were more likely observed at the VH. The mark-recapture study showed that D. setosum was found to displace further at the IH, and H. crassispina was more sedentary. Additionally, D. setosum was always observed in groups, whereas H. crassispina was always solitary. Discussion: The behaviors of sympatric urchins, Diadema savignyi, D. setosum and H. crassispina, differed in response to changes in the benthic, PeerJ, 11, art. no. e15511; 2023
Published: 2023

33. Mass Transfer from Mobile to Immobile Regions in Irregularly Shaped Micro-Channels at Low Reynolds Number

Author: Toyama, Kizuki, Togi, Fumina, Harada, Shusaku, Toyama, Kizuki, Togi, Fumina, and Harada, Shusaku
Abstract: Transient mass transfer in rough-walled micro-channels was investigated experimentally. We conducted experiments using rough-walled channels with various irregularities at small Reynolds number conditions. Mass transfer in the mainstream (mobile region) and dead water region (immobile region) were quantified using an image analysis technique based on absorption photometry. The experimental results showed that the solute dispersion in the mobile region was influenced by the irregular shape of the channel wall complicatedly. In contrast, mass transfer in the immobile region occurred by molecular diffusion independently on the wall roughness in our experimental conditions. The irregular shape of channel wall may enhance the mass transfer in mobile region by distorting the velocity distribution (Togi et al., 2020), while the solute redistribution to immobile region may suppress it in streamwise direction, just on a longer time scale. We developed a mass transfer model analogous to Mobile-Immobile model (MIM model) proposed by previous studies. The concept of the model is the same as the previous study (Zhou et al., 2019) and the coefficients of the model describing mass transfer in each region were quantified from the experimental results as functions of geometric characteristics of the rough-walled channel. In addition, mass transfer coefficient from mobile to immobile regions were derived mathematically based on the experimental results. The MIM model with the coefficients derived in this study well describes solute dispersion in variously shaped irregular channels quantitatively.
Published: 2023

34. La Reforma Laboral de los noventa: ¿Lección aprendida?

Author: Toyama Miyagusuku, Jorge, Caro Paccini, Eliana, Toyama Miyagusuku, Jorge, and Caro Paccini, Eliana
Abstract: 1. Presentación de los cambios normativos en la legislación del trabajo 1.1. Año 1990 a. Remuneración y otros ingresos b. Empleo y contratación c. Relaciones colectivas d. Obligaciones administrativas 1.2. Año 1991 a. Remuneración y otros ingresos b. Empleo y contratación c. Tiempo de trabajo d. Prestación de trabajo e. Obligaciones administrativas f. Aportaciones a cargo del empleador g. Relaciones colectivas 1.3. Año 1992 a. Remuneración y otros ingresos b. Empleo y contratación c. Tiempo de trabajo d. Relaciones colectivas e. Aportaciones a cargo del empleador f. Obligaciones del empleador 1.4. Año 1993 a. Empleo y contratación b. Insolvencia del empleador c. Aportaciones a cargo del empleador 1.5. 1994 a. Remuneración b. Tiempo de trabajo c. Aportaciones a cargo del empleador 1.6 Año 1995 a. Empleo y contratación b. Aportaciones a cargo del empleador 1.7 Año 1996 a. Remuneración y otros ingresos b. Empleo c. Tiempo de trabajo d. Obligaciones formales del empleador e. Aportaciones a cargo del empleador 1.8 Año 1997 a. Remuneraciones y otros ingresos b. Empleo c. Tiempo de trabajo d. Aportaciones a cargo del empleador 1.9 Año 1998 a. Remuneración y otros ingresos b. Empleo c. Obligaciones del empleador 1.1 O. Año 1999 a. Remuneración y otros ingresos b. Empleo c. Tiempo de trabajo d. Aportaciones a cargo del empleador 1.11. Año 2000 a. Remuneración y otros ingresos b. Empleo c. Tiempo de trabajo d. Aportaciones a cargo del empleador e. Obligaciones del empleador 1.12. Año 2001 a. Remuneración y otros ingresos b. Empleo c. Tiempo de trabajo d. Obligaciones del empleador e. Aportaciones a cargo del empleador f. Relaciones colectivas 2. Evaluación normativa: análisis de los "picos" de la reforma laboral 2.1. Los enfoques de la reforma laboral a. Contratación laboral b. Periodo de prueba c. Remuneraciones d. Beneficios sociales e. Tiempo de trabajo f. Condiciones de trabajo g. Extinción de la relación laboral h. Prestación por desempleo i. Relaciones colectivas de tra
Published: 2023

35. Seasonal Variability of the Surface Ocean Carbon Cycle: A Synthesis

Author: National Institute for Environmental Studies (Japan), Japan Agency for Marine-Earth Science and Technology, European Space Agency, Institute for Basic Science (South Korea), Research Council of Norway, National Oceanic and Atmospheric Administration (US), European Commission, Helmholtz Association, Environmental Restoration and Conservation Agency (Japan), Ministry of the Environment (Japan), Ministerio de Ciencia e Innovación (España), Rodgers, Keith B., Schwinger, Jörg, Fassbender, Andrea J., Landschützer, Peter, Yamaguchi, Ryohei, Frenzel, Hartmut, Stein, Karl, Müller, Jens Daniel, Goris, Nadine, Sharma, Sahil, Bushinsky, Seth, Chau, Thi-Tuyet-Trang, Gehlen, Marion, Gallego, M. Angeles, Gloege, Lucas, Gregor, Luke, Gruber, Nicolas, Hauck, Judith, Iida, Yosuke, Ishii, Masao, Keppler, Lydia, Kim, Ji-Eun, Schlunegger, Sarah, Tjiputra, Jerry, Toyama, Katsuya, Ayar, Pradeebane Vaittinada, Velo, A., National Institute for Environmental Studies (Japan), Japan Agency for Marine-Earth Science and Technology, European Space Agency, Institute for Basic Science (South Korea), Research Council of Norway, National Oceanic and Atmospheric Administration (US), European Commission, Helmholtz Association, Environmental Restoration and Conservation Agency (Japan), Ministry of the Environment (Japan), Ministerio de Ciencia e Innovación (España), Rodgers, Keith B., Schwinger, Jörg, Fassbender, Andrea J., Landschützer, Peter, Yamaguchi, Ryohei, Frenzel, Hartmut, Stein, Karl, Müller, Jens Daniel, Goris, Nadine, Sharma, Sahil, Bushinsky, Seth, Chau, Thi-Tuyet-Trang, Gehlen, Marion, Gallego, M. Angeles, Gloege, Lucas, Gregor, Luke, Gruber, Nicolas, Hauck, Judith, Iida, Yosuke, Ishii, Masao, Keppler, Lydia, Kim, Ji-Eun, Schlunegger, Sarah, Tjiputra, Jerry, Toyama, Katsuya, Ayar, Pradeebane Vaittinada, and Velo, A.
Abstract: The seasonal cycle is the dominant mode of variability in the air-sea CO2 flux in most regions of the global ocean, yet discrepancies between different seasonality estimates are rather large. As part of the Regional Carbon Cycle Assessment and Processes Phase 2 project (RECCAP2), we synthesize surface ocean pCO2 and air-sea CO2 flux seasonality from models and observation-based estimates, focusing on both a present-day climatology and decadal changes between the 1980s and 2010s. Four main findings emerge: First, global ocean biogeochemistry models (GOBMs) and observation-based estimates (pCO2 products) of surface pCO2 seasonality disagree in amplitude and phase, primarily due to discrepancies in the seasonal variability in surface DIC. Second, the seasonal cycle in pCO2 has increased in amplitude over the last three decades in both pCO2 products and GOBMs. Third, decadal increases in pCO2 seasonal cycle amplitudes in subtropical biomes for both pCO2 products and GOBMs are driven by increasing DIC concentrations stemming from the uptake of anthropogenic CO2 (Cant). In subpolar and Southern Ocean biomes, however, the seasonality change for GOBMs is dominated by Cant invasion, whereas for pCO2 products an indeterminate combination of Cant invasion and climate change modulates the changes. Fourth, biome-aggregated decadal changes in the amplitude of pCO2 seasonal variability are largely detectable against both mapping uncertainty (reducible) and natural variability uncertainty (irreducible), but not at the gridpoint scale over much of the northern subpolar oceans and over the Southern Ocean, underscoring the importance of sustained high-quality seasonally resolved measurements over these regions
Published: 2023

36. Online Harassment in Majority Contexts: Examining Harms and Remedies across Countries

Author: Schoenebeck, Sarita, Batool, Amna, Do, Giang, Darling, Sylvia, Grill, Gabriel, Wilkinson, Daricia, Khan, Mehtab, Toyama, Kentaro, Ashwell, Louise, Schoenebeck, Sarita, Batool, Amna, Do, Giang, Darling, Sylvia, Grill, Gabriel, Wilkinson, Daricia, Khan, Mehtab, Toyama, Kentaro, and Ashwell, Louise
Abstract: Online harassment is a global problem. This article examines perceptions of harm and preferences for remedies associated with online harassment with nearly 4000 participants in 14 countries around the world. The countries in this work reflect a range of identities and values, with a focus on those outside of North American and European contexts. Results show that perceptions of harm are higher among participants from all countries studied compared to the United States. Non-consensual sharing of sexual photos is consistently rated as harmful in all countries, while insults and rumors are perceived as more harmful in non-U.S. countries, especially harm to family reputation. Lower trust in other people and lower trust in sense of safety in one's neighborhood correlate with increased perceptions of harm of online harassment. In terms of remedies, participants in most countries prefer monetary compensation, apologies, and publicly revealing offender's identities compared to the U.S. Social media platform design and policy must consider regional values and norms, which may depart from U.S. centric-approaches.
Published: 2023
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37. Gemini: A Family of Highly Capable Multimodal Models

Author: Gemini Team, Anil, Rohan, Borgeaud, Sebastian, Alayrac, Jean-Baptiste, Yu, Jiahui, Soricut, Radu, Schalkwyk, Johan, Dai, Andrew M., Hauth, Anja, Millican, Katie, Silver, David, Johnson, Melvin, Antonoglou, Ioannis, Schrittwieser, Julian, Glaese, Amelia, Chen, Jilin, Pitler, Emily, Lillicrap, Timothy, Lazaridou, Angeliki, Firat, Orhan, Molloy, James, Isard, Michael, Barham, Paul R., Hennigan, Tom, Lee, Benjamin, Viola, Fabio, Reynolds, Malcolm, Xu, Yuanzhong, Doherty, Ryan, Collins, Eli, Meyer, Clemens, Rutherford, Eliza, Moreira, Erica, Ayoub, Kareem, Goel, Megha, Krawczyk, Jack, Du, Cosmo, Chi, Ed, Cheng, Heng-Tze, Ni, Eric, Shah, Purvi, Kane, Patrick, Chan, Betty, Faruqui, Manaal, Severyn, Aliaksei, Lin, Hanzhao, Li, YaGuang, Cheng, Yong, Ittycheriah, Abe, Mahdieh, Mahdis, Chen, Mia, Sun, Pei, Tran, Dustin, Bagri, Sumit, Lakshminarayanan, Balaji, Liu, Jeremiah, Orban, Andras, Güra, Fabian, Zhou, Hao, Song, Xinying, Boffy, Aurelien, Ganapathy, Harish, Zheng, Steven, Choe, HyunJeong, Weisz, Ágoston, Zhu, Tao, Lu, Yifeng, Gopal, Siddharth, Kahn, Jarrod, Kula, Maciej, Pitman, Jeff, Shah, Rushin, Taropa, Emanuel, Merey, Majd Al, Baeuml, Martin, Chen, Zhifeng, Shafey, Laurent El, Zhang, Yujing, Sercinoglu, Olcan, Tucker, George, Piqueras, Enrique, Krikun, Maxim, Barr, Iain, Savinov, Nikolay, Danihelka, Ivo, Roelofs, Becca, White, Anaïs, Andreassen, Anders, von Glehn, Tamara, Yagati, Lakshman, Kazemi, Mehran, Gonzalez, Lucas, Khalman, Misha, Sygnowski, Jakub, Frechette, Alexandre, Smith, Charlotte, Culp, Laura, Proleev, Lev, Luan, Yi, Chen, Xi, Lottes, James, Schucher, Nathan, Lebron, Federico, Rrustemi, Alban, Clay, Natalie, Crone, Phil, Kocisky, Tomas, Zhao, Jeffrey, Perz, Bartek, Yu, Dian, Howard, Heidi, Bloniarz, Adam, Rae, Jack W., Lu, Han, Sifre, Laurent, Maggioni, Marcello, Alcober, Fred, Garrette, Dan, Barnes, Megan, Thakoor, Shantanu, Austin, Jacob, Barth-Maron, Gabriel, Wong, William, Joshi, Rishabh, Chaabouni, Rahma, Fatiha, Deeni, Ahuja, Arun, Tomar, Gaurav Singh, Senter, Evan, Chadwick, Martin, Kornakov, Ilya, Attaluri, Nithya, Iturrate, Iñaki, Liu, Ruibo, Li, Yunxuan, Cogan, Sarah, Chen, Jeremy, Jia, Chao, Gu, Chenjie, Zhang, Qiao, Grimstad, Jordan, Hartman, Ale Jakse, Garcia, Xavier, Pillai, Thanumalayan Sankaranarayana, Devlin, Jacob, Laskin, Michael, Casas, Diego de Las, Valter, Dasha, Tao, Connie, Blanco, Lorenzo, Badia, Adrià Puigdomènech, Reitter, David, Chen, Mianna, Brennan, Jenny, Rivera, Clara, Brin, Sergey, Iqbal, Shariq, Surita, Gabriela, Labanowski, Jane, Rao, Abhi, Winkler, Stephanie, Parisotto, Emilio, Gu, Yiming, Olszewska, Kate, Addanki, Ravi, Miech, Antoine, Louis, Annie, Teplyashin, Denis, Brown, Geoff, Catt, Elliot, Balaguer, Jan, Xiang, Jackie, Wang, Pidong, Ashwood, Zoe, Briukhov, Anton, Webson, Albert, Ganapathy, Sanjay, Sanghavi, Smit, Kannan, Ajay, Chang, Ming-Wei, Stjerngren, Axel, Djolonga, Josip, Sun, Yuting, Bapna, Ankur, Aitchison, Matthew, Pejman, Pedram, Michalewski, Henryk, Yu, Tianhe, Wang, Cindy, Love, Juliette, Ahn, Junwhan, Bloxwich, Dawn, Han, Kehang, Humphreys, Peter, Sellam, Thibault, Bradbury, James, Godbole, Varun, Samangooei, Sina, Damoc, Bogdan, Kaskasoli, Alex, Arnold, Sébastien M. R., Vasudevan, Vijay, Agrawal, Shubham, Riesa, Jason, Lepikhin, Dmitry, Tanburn, Richard, Srinivasan, Srivatsan, Lim, Hyeontaek, Hodkinson, Sarah, Shyam, Pranav, Ferret, Johan, Hand, Steven, Garg, Ankush, Paine, Tom Le, Li, Jian, Li, Yujia, Giang, Minh, Neitz, Alexander, Abbas, Zaheer, York, Sarah, Reid, Machel, Cole, Elizabeth, Chowdhery, Aakanksha, Das, Dipanjan, Rogozińska, Dominika, Nikolaev, Vitaliy, Sprechmann, Pablo, Nado, Zachary, Zilka, Lukas, Prost, Flavien, He, Luheng, Monteiro, Marianne, Mishra, Gaurav, Welty, Chris, Newlan, Josh, Jia, Dawei, Allamanis, Miltiadis, Hu, Clara Huiyi, de Liedekerke, Raoul, Gilmer, Justin, Saroufim, Carl, Rijhwani, Shruti, Hou, Shaobo, Shrivastava, Disha, Baddepudi, Anirudh, Goldin, Alex, Ozturel, Adnan, Cassirer, Albin, Xu, Yunhan, Sohn, Daniel, Sachan, Devendra, Amplayo, Reinald Kim, Swanson, Craig, Petrova, Dessie, Narayan, Shashi, Guez, Arthur, Brahma, Siddhartha, Landon, Jessica, Patel, Miteyan, Zhao, Ruizhe, Villela, Kevin, Wang, Luyu, Jia, Wenhao, Rahtz, Matthew, Giménez, Mai, Yeung, Legg, Keeling, James, Georgiev, Petko, Mincu, Diana, Wu, Boxi, Haykal, Salem, Saputro, Rachel, Vodrahalli, Kiran, Qin, James, Cankara, Zeynep, Sharma, Abhanshu, Fernando, Nick, Hawkins, Will, Neyshabur, Behnam, Kim, Solomon, Hutter, Adrian, Agrawal, Priyanka, Castro-Ros, Alex, Driessche, George van den, Wang, Tao, Yang, Fan, Chang, Shuo-yiin, Komarek, Paul, McIlroy, Ross, Lučić, Mario, Zhang, Guodong, Farhan, Wael, Sharman, Michael, Natsev, Paul, Michel, Paul, Bansal, Yamini, Qiao, Siyuan, Cao, Kris, Shakeri, Siamak, Butterfield, Christina, Chung, Justin, Rubenstein, Paul Kishan, Agrawal, Shivani, Mensch, Arthur, Soparkar, Kedar, Lenc, Karel, Chung, Timothy, Pope, Aedan, Maggiore, Loren, Kay, Jackie, Jhakra, Priya, Wang, Shibo, Maynez, Joshua, Phuong, Mary, Tobin, Taylor, Tacchetti, Andrea, Trebacz, Maja, Robinson, Kevin, Katariya, Yash, Riedel, Sebastian, Bailey, Paige, Xiao, Kefan, Ghelani, Nimesh, Aroyo, Lora, Slone, Ambrose, Houlsby, Neil, Xiong, Xuehan, Yang, Zhen, Gribovskaya, Elena, Adler, Jonas, Wirth, Mateo, Lee, Lisa, Li, Music, Kagohara, Thais, Pavagadhi, Jay, Bridgers, Sophie, Bortsova, Anna, Ghemawat, Sanjay, Ahmed, Zafarali, Liu, Tianqi, Powell, Richard, Bolina, Vijay, Iinuma, Mariko, Zablotskaia, Polina, Besley, James, Chung, Da-Woon, Dozat, Timothy, Comanescu, Ramona, Si, Xiance, Greer, Jeremy, Su, Guolong, Polacek, Martin, Kaufman, Raphaël Lopez, Tokumine, Simon, Hu, Hexiang, Buchatskaya, Elena, Miao, Yingjie, Elhawaty, Mohamed, Siddhant, Aditya, Tomasev, Nenad, Xing, Jinwei, Greer, Christina, Miller, Helen, Ashraf, Shereen, Roy, Aurko, Zhang, Zizhao, Ma, Ada, Filos, Angelos, Besta, Milos, Blevins, Rory, Klimenko, Ted, Yeh, Chih-Kuan, Changpinyo, Soravit, Mu, Jiaqi, Chang, Oscar, Pajarskas, Mantas, Muir, Carrie, Cohen, Vered, Lan, Charline Le, Haridasan, Krishna, Marathe, Amit, Hansen, Steven, Douglas, Sholto, Samuel, Rajkumar, Wang, Mingqiu, Austin, Sophia, Lan, Chang, Jiang, Jiepu, Chiu, Justin, Lorenzo, Jaime Alonso, Sjösund, Lars Lowe, Cevey, Sébastien, Gleicher, Zach, Avrahami, Thi, Boral, Anudhyan, Srinivasan, Hansa, Selo, Vittorio, May, Rhys, Aisopos, Konstantinos, Hussenot, Léonard, Soares, Livio Baldini, Baumli, Kate, Chang, Michael B., Recasens, Adrià, Caine, Ben, Pritzel, Alexander, Pavetic, Filip, Pardo, Fabio, Gergely, Anita, Frye, Justin, Ramasesh, Vinay, Horgan, Dan, Badola, Kartikeya, Kassner, Nora, Roy, Subhrajit, Dyer, Ethan, Campos, Víctor Campos, Tomala, Alex, Tang, Yunhao, Badawy, Dalia El, White, Elspeth, Mustafa, Basil, Lang, Oran, Jindal, Abhishek, Vikram, Sharad, Gong, Zhitao, Caelles, Sergi, Hemsley, Ross, Thornton, Gregory, Feng, Fangxiaoyu, Stokowiec, Wojciech, Zheng, Ce, Thacker, Phoebe, Ünlü, Çağlar, Zhang, Zhishuai, Saleh, Mohammad, Svensson, James, Bileschi, Max, Patil, Piyush, Anand, Ankesh, Ring, Roman, Tsihlas, Katerina, Vezer, Arpi, Selvi, Marco, Shevlane, Toby, Rodriguez, Mikel, Kwiatkowski, Tom, Daruki, Samira, Rong, Keran, Dafoe, Allan, FitzGerald, Nicholas, Gu-Lemberg, Keren, Khan, Mina, Hendricks, Lisa Anne, Pellat, Marie, Feinberg, Vladimir, Cobon-Kerr, James, Sainath, Tara, Rauh, Maribeth, Hashemi, Sayed Hadi, Ives, Richard, Hasson, Yana, Noland, Eric, Cao, Yuan, Byrd, Nathan, Hou, Le, Wang, Qingze, Sottiaux, Thibault, Paganini, Michela, Lespiau, Jean-Baptiste, Moufarek, Alexandre, Hassan, Samer, Shivakumar, Kaushik, van Amersfoort, Joost, Mandhane, Amol, Joshi, Pratik, Goyal, Anirudh, Tung, Matthew, Brock, Andrew, Sheahan, Hannah, Misra, Vedant, Li, Cheng, Rakićević, Nemanja, Dehghani, Mostafa, Liu, Fangyu, Mittal, Sid, Oh, Junhyuk, Noury, Seb, Sezener, Eren, Huot, Fantine, Lamm, Matthew, De Cao, Nicola, Chen, Charlie, Mudgal, Sidharth, Stella, Romina, Brooks, Kevin, Vasudevan, Gautam, Liu, Chenxi, Chain, Mainak, Melinkeri, Nivedita, Cohen, Aaron, Wang, Venus, Seymore, Kristie, Zubkov, Sergey, Goel, Rahul, Yue, Summer, Krishnakumaran, Sai, Albert, Brian, Hurley, Nate, Sano, Motoki, Mohananey, Anhad, Joughin, Jonah, Filonov, Egor, Kępa, Tomasz, Eldawy, Yomna, Lim, Jiawern, Rishi, Rahul, Badiezadegan, Shirin, Bos, Taylor, Chang, Jerry, Jain, Sanil, Padmanabhan, Sri Gayatri Sundara, Puttagunta, Subha, Krishna, Kalpesh, Baker, Leslie, Kalb, Norbert, Bedapudi, Vamsi, Kurzrok, Adam, Lei, Shuntong, Yu, Anthony, Litvin, Oren, Zhou, Xiang, Wu, Zhichun, Sobell, Sam, Siciliano, Andrea, Papir, Alan, Neale, Robby, Bragagnolo, Jonas, Toor, Tej, Chen, Tina, Anklin, Valentin, Wang, Feiran, Feng, Richie, Gholami, Milad, Ling, Kevin, Liu, Lijuan, Walter, Jules, Moghaddam, Hamid, Kishore, Arun, Adamek, Jakub, Mercado, Tyler, Mallinson, Jonathan, Wandekar, Siddhinita, Cagle, Stephen, Ofek, Eran, Garrido, Guillermo, Lombriser, Clemens, Mukha, Maksim, Sun, Botu, Mohammad, Hafeezul Rahman, Matak, Josip, Qian, Yadi, Peswani, Vikas, Janus, Pawel, Yuan, Quan, Schelin, Leif, David, Oana, Garg, Ankur, He, Yifan, Duzhyi, Oleksii, Älgmyr, Anton, Lottaz, Timothée, Li, Qi, Yadav, Vikas, Xu, Luyao, Chinien, Alex, Shivanna, Rakesh, Chuklin, Aleksandr, Li, Josie, Spadine, Carrie, Wolfe, Travis, Mohamed, Kareem, Das, Subhabrata, Dai, Zihang, He, Kyle, von Dincklage, Daniel, Upadhyay, Shyam, Maurya, Akanksha, Chi, Luyan, Krause, Sebastian, Salama, Khalid, Rabinovitch, Pam G, M, Pavan Kumar Reddy, Selvan, Aarush, Dektiarev, Mikhail, Ghiasi, Golnaz, Guven, Erdem, Gupta, Himanshu, Liu, Boyi, Sharma, Deepak, Shtacher, Idan Heimlich, Paul, Shachi, Akerlund, Oscar, Aubet, François-Xavier, Huang, Terry, Zhu, Chen, Zhu, Eric, Teixeira, Elico, Fritze, Matthew, Bertolini, Francesco, Marinescu, Liana-Eleonora, Bölle, Martin, Paulus, Dominik, Gupta, Khyatti, Latkar, Tejasi, Chang, Max, Sanders, Jason, Wilson, Roopa, Wu, Xuewei, Tan, Yi-Xuan, Thiet, Lam Nguyen, Doshi, Tulsee, Lall, Sid, Mishra, Swaroop, Chen, Wanming, Luong, Thang, Benjamin, Seth, Lee, Jasmine, Andrejczuk, Ewa, Rabiej, Dominik, Ranjan, Vipul, Styrc, Krzysztof, Yin, Pengcheng, Simon, Jon, Harriott, Malcolm Rose, Bansal, Mudit, Robsky, Alexei, Bacon, Geoff, Greene, David, Mirylenka, Daniil, Zhou, Chen, Sarvana, Obaid, Goyal, Abhimanyu, Andermatt, Samuel, Siegler, Patrick, Horn, Ben, Israel, Assaf, Pongetti, Francesco, Chen, Chih-Wei "Louis", Selvatici, Marco, Silva, Pedro, Wang, Kathie, Tolins, Jackson, Guu, Kelvin, Yogev, Roey, Cai, Xiaochen, Agostini, Alessandro, Shah, Maulik, Nguyen, Hung, Donnaile, Noah Ó, Pereira, Sébastien, Friso, Linda, Stambler, Adam, Kuang, Chenkai, Romanikhin, Yan, Geller, Mark, Yan, ZJ, Jang, Kane, Lee, Cheng-Chun, Fica, Wojciech, Malmi, Eric, Tan, Qijun, Banica, Dan, Balle, Daniel, Pham, Ryan, Huang, Yanping, Avram, Diana, Shi, Hongzhi, Singh, Jasjot, Hidey, Chris, Ahuja, Niharika, Saxena, Pranab, Dooley, Dan, Potharaju, Srividya Pranavi, O'Neill, Eileen, Gokulchandran, Anand, Foley, Ryan, Zhao, Kai, Dusenberry, Mike, Liu, Yuan, Mehta, Pulkit, Kotikalapudi, Ragha, Safranek-Shrader, Chalence, Goodman, Andrew, Kessinger, Joshua, Globen, Eran, Kolhar, Prateek, Gorgolewski, Chris, Ibrahim, Ali, Song, Yang, Eichenbaum, Ali, Brovelli, Thomas, Potluri, Sahitya, Lahoti, Preethi, Baetu, Cip, Ghorbani, Ali, Chen, Charles, Crawford, Andy, Pal, Shalini, Sridhar, Mukund, Gurita, Petru, Mujika, Asier, Petrovski, Igor, Cedoz, Pierre-Louis, Li, Chenmei, Chen, Shiyuan, Santo, Niccolò Dal, Goyal, Siddharth, Punjabi, Jitesh, Kappaganthu, Karthik, Kwak, Chester, LV, Pallavi, Velury, Sarmishta, Choudhury, Himadri, Hall, Jamie, Shah, Premal, Figueira, Ricardo, Thomas, Matt, Lu, Minjie, Zhou, Ting, Kumar, Chintu, Jurdi, Thomas, Chikkerur, Sharat, Ma, Yenai, Yu, Adams, Kwak, Soo, Ähdel, Victor, Rajayogam, Sujeevan, Choma, Travis, Liu, Fei, Barua, Aditya, Ji, Colin, Park, Ji Ho, Hellendoorn, Vincent, Bailey, Alex, Bilal, Taylan, Zhou, Huanjie, Khatir, Mehrdad, Sutton, Charles, Rzadkowski, Wojciech, Macintosh, Fiona, Shagin, Konstantin, Medina, Paul, Liang, Chen, Zhou, Jinjing, Shah, Pararth, Bi, Yingying, Dankovics, Attila, Banga, Shipra, Lehmann, Sabine, Bredesen, Marissa, Lin, Zifan, Hoffmann, John Eric, Lai, Jonathan, Chung, Raynald, Yang, Kai, Balani, Nihal, Bražinskas, Arthur, Sozanschi, Andrei, Hayes, Matthew, Alcalde, Héctor Fernández, Makarov, Peter, Chen, Will, Stella, Antonio, Snijders, Liselotte, Mandl, Michael, Kärrman, Ante, Nowak, Paweł, Wu, Xinyi, Dyck, Alex, Vaidyanathan, Krishnan, R, Raghavender, Mallet, Jessica, Rudominer, Mitch, Johnston, Eric, Mittal, Sushil, Udathu, Akhil, Christensen, Janara, Verma, Vishal, Irving, Zach, Santucci, Andreas, Elsayed, Gamaleldin, Davoodi, Elnaz, Georgiev, Marin, Tenney, Ian, Hua, Nan, Cideron, Geoffrey, Leurent, Edouard, Alnahlawi, Mahmoud, Georgescu, Ionut, Wei, Nan, Zheng, Ivy, Scandinaro, Dylan, Jiang, Heinrich, Snoek, Jasper, Sundararajan, Mukund, Wang, Xuezhi, Ontiveros, Zack, Karo, Itay, Cole, Jeremy, Rajashekhar, Vinu, Tumeh, Lara, Ben-David, Eyal, Jain, Rishub, Uesato, Jonathan, Datta, Romina, Bunyan, Oskar, Wu, Shimu, Zhang, John, Stanczyk, Piotr, Zhang, Ye, Steiner, David, Naskar, Subhajit, Azzam, Michael, Johnson, Matthew, Paszke, Adam, Chiu, Chung-Cheng, Elias, Jaume Sanchez, Mohiuddin, Afroz, Muhammad, Faizan, Miao, Jin, Lee, Andrew, Vieillard, Nino, Park, Jane, Zhang, Jiageng, Stanway, Jeff, Garmon, Drew, Karmarkar, Abhijit, Dong, Zhe, Lee, Jong, Kumar, Aviral, Zhou, Luowei, Evens, Jonathan, Isaac, William, Irving, Geoffrey, Loper, Edward, Fink, Michael, Arkatkar, Isha, Chen, Nanxin, Shafran, Izhak, Petrychenko, Ivan, Chen, Zhe, Jia, Johnson, Levskaya, Anselm, Zhu, Zhenkai, Grabowski, Peter, Mao, Yu, Magni, Alberto, Yao, Kaisheng, Snaider, Javier, Casagrande, Norman, Palmer, Evan, Suganthan, Paul, Castaño, Alfonso, Giannoumis, Irene, Kim, Wooyeol, Rybiński, Mikołaj, Sreevatsa, Ashwin, Prendki, Jennifer, Soergel, David, Goedeckemeyer, Adrian, Gierke, Willi, Jafari, Mohsen, Gaba, Meenu, Wiesner, Jeremy, Wright, Diana Gage, Wei, Yawen, Vashisht, Harsha, Kulizhskaya, Yana, Hoover, Jay, Le, Maigo, Li, Lu, Iwuanyanwu, Chimezie, Liu, Lu, Ramirez, Kevin, Khorlin, Andrey, Cui, Albert, LIN, Tian, Wu, Marcus, Aguilar, Ricardo, Pallo, Keith, Chakladar, Abhishek, Perng, Ginger, Abellan, Elena Allica, Zhang, Mingyang, Dasgupta, Ishita, Kushman, Nate, Penchev, Ivo, Repina, Alena, Wu, Xihui, van der Weide, Tom, Ponnapalli, Priya, Kaplan, Caroline, Simsa, Jiri, Li, Shuangfeng, Dousse, Olivier, Piper, Jeff, Ie, Nathan, Pasumarthi, Rama, Lintz, Nathan, Vijayakumar, Anitha, Andor, Daniel, Valenzuela, Pedro, Lui, Minnie, Paduraru, Cosmin, Peng, Daiyi, Lee, Katherine, Zhang, Shuyuan, Greene, Somer, Nguyen, Duc Dung, Kurylowicz, Paula, Hardin, Cassidy, Dixon, Lucas, Janzer, Lili, Choo, Kiam, Feng, Ziqiang, Zhang, Biao, Singhal, Achintya, Du, Dayou, McKinnon, Dan, Antropova, Natasha, Bolukbasi, Tolga, Keller, Orgad, Reid, David, Finchelstein, Daniel, Raad, Maria Abi, Crocker, Remi, Hawkins, Peter, Dadashi, Robert, Gaffney, Colin, Franko, Ken, Bulanova, Anna, Leblond, Rémi, Chung, Shirley, Askham, Harry, Cobo, Luis C., Xu, Kelvin, Fischer, Felix, Xu, Jun, Sorokin, Christina, Alberti, Chris, Lin, Chu-Cheng, Evans, Colin, Dimitriev, Alek, Forbes, Hannah, Banarse, Dylan, Tung, Zora, Omernick, Mark, Bishop, Colton, Sterneck, Rachel, Jain, Rohan, Xia, Jiawei, Amid, Ehsan, Piccinno, Francesco, Wang, Xingyu, Banzal, Praseem, Mankowitz, Daniel J., Polozov, Alex, Krakovna, Victoria, Brown, Sasha, Bateni, MohammadHossein, Duan, Dennis, Firoiu, Vlad, Thotakuri, Meghana, Natan, Tom, Geist, Matthieu, Girgin, Ser tan, Li, Hui, Ye, Jiayu, Roval, Ofir, Tojo, Reiko, Kwong, Michael, Lee-Thorp, James, Yew, Christopher, Sinopalnikov, Danila, Ramos, Sabela, Mellor, John, Sharma, Abhishek, Wu, Kathy, Miller, David, Sonnerat, Nicolas, Vnukov, Denis, Greig, Rory, Beattie, Jennifer, Caveness, Emily, Bai, Libin, Eisenschlos, Julian, Korchemniy, Alex, Tsai, Tomy, Jasarevic, Mimi, Kong, Weize, Dao, Phuong, Zheng, Zeyu, Liu, Frederick, Zhu, Rui, Teh, Tian Huey, Sanmiya, Jason, Gladchenko, Evgeny, Trdin, Nejc, Toyama, Daniel, Rosen, Evan, Tavakkol, Sasan, Xue, Linting, Elkind, Chen, Woodman, Oliver, Carpenter, John, Papamakarios, George, Kemp, Rupert, Kafle, Sushant, Grunina, Tanya, Sinha, Rishika, Talbert, Alice, Wu, Diane, Owusu-Afriyie, Denese, Thornton, Chloe, Pont-Tuset, Jordi, Narayana, Pradyumna, Li, Jing, Fatehi, Saaber, Wieting, John, Ajmeri, Omar, Uria, Benigno, Ko, Yeongil, Knight, Laura, Héliou, Amélie, Niu, Ning, Gu, Shane, Pang, Chenxi, Li, Yeqing, Levine, Nir, Stolovich, Ariel, Santamaria-Fernandez, Rebeca, Goenka, Sonam, Yustalim, Wenny, Strudel, Robin, Elqursh, Ali, Deck, Charlie, Lee, Hyo, Li, Zonglin, Levin, Kyle, Hoffmann, Raphael, Holtmann-Rice, Dan, Bachem, Olivier, Arora, Sho, Koh, Christy, Yeganeh, Soheil Hassas, Põder, Siim, Tariq, Mukarram, Sun, Yanhua, Ionita, Lucian, Seyedhosseini, Mojtaba, Tafti, Pouya, Liu, Zhiyu, Gulati, Anmol, Liu, Jasmine, Ye, Xinyu, Chrzaszcz, Bart, Wang, Lily, Sethi, Nikhil, Li, Tianrun, Brown, Ben, Singh, Shreya, Fan, Wei, Parisi, Aaron, Stanton, Joe, Koverkathu, Vinod, Choquette-Choo, Christopher A., Li, Yunjie, Lu, TJ, Shroff, Prakash, Varadarajan, Mani, Bahargam, Sanaz, Willoughby, Rob, Gaddy, David, Desjardins, Guillaume, Cornero, Marco, Robenek, Brona, Mittal, Bhavishya, Albrecht, Ben, Shenoy, Ashish, Moiseev, Fedor, Jacobsson, Henrik, Ghaffarkhah, Alireza, Rivière, Morgane, Walton, Alanna, Crepy, Clément, Parrish, Alicia, Zhou, Zongwei, Farabet, Clement, Radebaugh, Carey, Srinivasan, Praveen, van der Salm, Claudia, Fidjeland, Andreas, Scellato, Salvatore, Latorre-Chimoto, Eri, Klimczak-Plucińska, Hanna, Bridson, David, de Cesare, Dario, Hudson, Tom, Mendolicchio, Piermaria, Walker, Lexi, Morris, Alex, Mauger, Matthew, Guseynov, Alexey, Reid, Alison, Odoom, Seth, Loher, Lucia, Cotruta, Victor, Yenugula, Madhavi, Grewe, Dominik, Petrushkina, Anastasia, Duerig, Tom, Sanchez, Antonio, Yadlowsky, Steve, Shen, Amy, Globerson, Amir, Webb, Lynette, Dua, Sahil, Li, Dong, Bhupatiraju, Surya, Hurt, Dan, Qureshi, Haroon, Agarwal, Ananth, Shani, Tomer, Eyal, Matan, Khare, Anuj, Belle, Shreyas Rammohan, Wang, Lei, Tekur, Chetan, Kale, Mihir Sanjay, Wei, Jinliang, Sang, Ruoxin, Saeta, Brennan, Liechty, Tyler, Sun, Yi, Zhao, Yao, Lee, Stephan, Nayak, Pandu, Fritz, Doug, Vuyyuru, Manish Reddy, Aslanides, John, Vyas, Nidhi, Wicke, Martin, Ma, Xiao, Eltyshev, Evgenii, Martin, Nina, Cate, Hardie, Manyika, James, Amiri, Keyvan, Kim, Yelin, Xiong, Xi, Kang, Kai, Luisier, Florian, Tripuraneni, Nilesh, Madras, David, Guo, Mandy, Waters, Austin, Wang, Oliver, Ainslie, Joshua, Baldridge, Jason, Zhang, Han, Pruthi, Garima, Bauer, Jakob, Yang, Feng, Mansour, Riham, Gelman, Jason, Xu, Yang, Polovets, George, Liu, Ji, Cai, Honglong, Chen, Warren, Sheng, XiangHai, Xue, Emily, Ozair, Sherjil, Angermueller, Christof, Li, Xiaowei, Sinha, Anoop, Wang, Weiren, Wiesinger, Julia, Koukoumidis, Emmanouil, Tian, Yuan, Iyer, Anand, Gurumurthy, Madhu, Goldenson, Mark, Shah, Parashar, Blake, MK, Yu, Hongkun, Urbanowicz, Anthony, Palomaki, Jennimaria, Fernando, Chrisantha, Durden, Ken, Mehta, Harsh, Momchev, Nikola, Rahimtoroghi, Elahe, Georgaki, Maria, Raul, Amit, Ruder, Sebastian, Redshaw, Morgan, Lee, Jinhyuk, Zhou, Denny, Jalan, Komal, Li, Dinghua, Hechtman, Blake, Schuh, Parker, Nasr, Milad, Milan, Kieran, Mikulik, Vladimir, Franco, Juliana, Green, Tim, Nguyen, Nam, Kelley, Joe, Mahendru, Aroma, Hu, Andrea, Howland, Joshua, Vargas, Ben, Hui, Jeffrey, Bansal, Kshitij, Rao, Vikram, Ghiya, Rakesh, Wang, Emma, Ye, Ke, Sarr, Jean Michel, Preston, Melanie Moranski, Elish, Madeleine, Li, Steve, Kaku, Aakash, Gupta, Jigar, Pasupat, Ice, Juan, Da-Cheng, Someswar, Milan, M., Tejvi, Chen, Xinyun, Amini, Aida, Fabrikant, Alex, Chu, Eric, Dong, Xuanyi, Muthal, Amruta, Buthpitiya, Senaka, Jauhari, Sarthak, Khandelwal, Urvashi, Hitron, Ayal, Ren, Jie, Rinaldi, Larissa, Drath, Shahar, Dabush, Avigail, Jiang, Nan-Jiang, Godhia, Harshal, Sachs, Uli, Chen, Anthony, Fan, Yicheng, Taitelbaum, Hagai, Noga, Hila, Dai, Zhuyun, Wang, James, Hamer, Jenny, Ferng, Chun-Sung, Elkind, Chenel, Atias, Aviel, Lee, Paulina, Listík, Vít, Carlen, Mathias, van de Kerkhof, Jan, Pikus, Marcin, Zaher, Krunoslav, Müller, Paul, Zykova, Sasha, Stefanec, Richard, Gatsko, Vitaly, Hirnschall, Christoph, Sethi, Ashwin, Xu, Xingyu Federico, Ahuja, Chetan, Tsai, Beth, Stefanoiu, Anca, Feng, Bo, Dhandhania, Keshav, Katyal, Manish, Gupta, Akshay, Parulekar, Atharva, Pitta, Divya, Zhao, Jing, Bhatia, Vivaan, Bhavnani, Yashodha, Alhadlaq, Omar, Li, Xiaolin, Danenberg, Peter, Tu, Dennis, Pine, Alex, Filippova, Vera, Ghosh, Abhipso, Limonchik, Ben, Urala, Bhargava, Lanka, Chaitanya Krishna, Clive, Derik, Li, Edward, Wu, Hao, Hongtongsak, Kevin, Li, Ianna, Thakkar, Kalind, Omarov, Kuanysh, Majmundar, Kushal, Alverson, Michael, Kucharski, Michael, Patel, Mohak, Jain, Mudit, Zabelin, Maksim, Pelagatti, Paolo, Kohli, Rohan, Kumar, Saurabh, Kim, Joseph, Sankar, Swetha, Shah, Vineet, Ramachandruni, Lakshmi, Zeng, Xiangkai, Bariach, Ben, Weidinger, Laura, Vu, Tu, Subramanya, Amar, Hsiao, Sissie, Hassabis, Demis, Kavukcuoglu, Koray, Sadovsky, Adam, Le, Quoc, Strohman, Trevor, Wu, Yonghui, Petrov, Slav, Dean, Jeffrey, Vinyals, Oriol, Gemini Team, Anil, Rohan, Borgeaud, Sebastian, Alayrac, Jean-Baptiste, Yu, Jiahui, Soricut, Radu, Schalkwyk, Johan, Dai, Andrew M., Hauth, Anja, Millican, Katie, Silver, David, Johnson, Melvin, Antonoglou, Ioannis, Schrittwieser, Julian, Glaese, Amelia, Chen, Jilin, Pitler, Emily, Lillicrap, Timothy, Lazaridou, Angeliki, Firat, Orhan, Molloy, James, Isard, Michael, Barham, Paul R., Hennigan, Tom, Lee, Benjamin, Viola, Fabio, Reynolds, Malcolm, Xu, Yuanzhong, Doherty, Ryan, Collins, Eli, Meyer, Clemens, Rutherford, Eliza, Moreira, Erica, Ayoub, Kareem, Goel, Megha, Krawczyk, Jack, Du, Cosmo, Chi, Ed, Cheng, Heng-Tze, Ni, Eric, Shah, Purvi, Kane, Patrick, Chan, Betty, Faruqui, Manaal, Severyn, Aliaksei, Lin, Hanzhao, Li, YaGuang, Cheng, Yong, Ittycheriah, Abe, Mahdieh, Mahdis, Chen, Mia, Sun, Pei, Tran, Dustin, Bagri, Sumit, Lakshminarayanan, Balaji, Liu, Jeremiah, Orban, Andras, Güra, Fabian, Zhou, Hao, Song, Xinying, Boffy, Aurelien, Ganapathy, Harish, Zheng, Steven, Choe, HyunJeong, Weisz, Ágoston, Zhu, Tao, Lu, Yifeng, Gopal, Siddharth, Kahn, Jarrod, Kula, Maciej, Pitman, Jeff, Shah, Rushin, Taropa, Emanuel, Merey, Majd Al, Baeuml, Martin, Chen, Zhifeng, Shafey, Laurent El, Zhang, Yujing, Sercinoglu, Olcan, Tucker, George, Piqueras, Enrique, Krikun, Maxim, Barr, Iain, Savinov, Nikolay, Danihelka, Ivo, Roelofs, Becca, White, Anaïs, Andreassen, Anders, von Glehn, Tamara, Yagati, Lakshman, Kazemi, Mehran, Gonzalez, Lucas, Khalman, Misha, Sygnowski, Jakub, Frechette, Alexandre, Smith, Charlotte, Culp, Laura, Proleev, Lev, Luan, Yi, Chen, Xi, Lottes, James, Schucher, Nathan, Lebron, Federico, Rrustemi, Alban, Clay, Natalie, Crone, Phil, Kocisky, Tomas, Zhao, Jeffrey, Perz, Bartek, Yu, Dian, Howard, Heidi, Bloniarz, Adam, Rae, Jack W., Lu, Han, Sifre, Laurent, Maggioni, Marcello, Alcober, Fred, Garrette, Dan, Barnes, Megan, Thakoor, Shantanu, Austin, Jacob, Barth-Maron, Gabriel, Wong, William, Joshi, Rishabh, Chaabouni, Rahma, Fatiha, Deeni, Ahuja, Arun, Tomar, Gaurav Singh, Senter, Evan, Chadwick, Martin, Kornakov, Ilya, Attaluri, Nithya, Iturrate, Iñaki, Liu, Ruibo, Li, Yunxuan, Cogan, Sarah, Chen, Jeremy, Jia, Chao, Gu, Chenjie, Zhang, Qiao, Grimstad, Jordan, Hartman, Ale Jakse, Garcia, Xavier, Pillai, Thanumalayan Sankaranarayana, Devlin, Jacob, Laskin, Michael, Casas, Diego de Las, Valter, Dasha, Tao, Connie, Blanco, Lorenzo, Badia, Adrià Puigdomènech, Reitter, David, Chen, Mianna, Brennan, Jenny, Rivera, Clara, Brin, Sergey, Iqbal, Shariq, Surita, Gabriela, Labanowski, Jane, Rao, Abhi, Winkler, Stephanie, Parisotto, Emilio, Gu, Yiming, Olszewska, Kate, Addanki, Ravi, Miech, Antoine, Louis, Annie, Teplyashin, Denis, Brown, Geoff, Catt, Elliot, Balaguer, Jan, Xiang, Jackie, Wang, Pidong, Ashwood, Zoe, Briukhov, Anton, Webson, Albert, Ganapathy, Sanjay, Sanghavi, Smit, Kannan, Ajay, Chang, Ming-Wei, Stjerngren, Axel, Djolonga, Josip, Sun, Yuting, Bapna, Ankur, Aitchison, Matthew, Pejman, Pedram, Michalewski, Henryk, Yu, Tianhe, Wang, Cindy, Love, Juliette, Ahn, Junwhan, Bloxwich, Dawn, Han, Kehang, Humphreys, Peter, Sellam, Thibault, Bradbury, James, Godbole, Varun, Samangooei, Sina, Damoc, Bogdan, Kaskasoli, Alex, Arnold, Sébastien M. R., Vasudevan, Vijay, Agrawal, Shubham, Riesa, Jason, Lepikhin, Dmitry, Tanburn, Richard, Srinivasan, Srivatsan, Lim, Hyeontaek, Hodkinson, Sarah, Shyam, Pranav, Ferret, Johan, Hand, Steven, Garg, Ankush, Paine, Tom Le, Li, Jian, Li, Yujia, Giang, Minh, Neitz, Alexander, Abbas, Zaheer, York, Sarah, Reid, Machel, Cole, Elizabeth, Chowdhery, Aakanksha, Das, Dipanjan, Rogozińska, Dominika, Nikolaev, Vitaliy, Sprechmann, Pablo, Nado, Zachary, Zilka, Lukas, Prost, Flavien, He, Luheng, Monteiro, Marianne, Mishra, Gaurav, Welty, Chris, Newlan, Josh, Jia, Dawei, Allamanis, Miltiadis, Hu, Clara Huiyi, de Liedekerke, Raoul, Gilmer, Justin, Saroufim, Carl, Rijhwani, Shruti, Hou, Shaobo, Shrivastava, Disha, Baddepudi, Anirudh, Goldin, Alex, Ozturel, Adnan, Cassirer, Albin, Xu, Yunhan, Sohn, Daniel, Sachan, Devendra, Amplayo, Reinald Kim, Swanson, Craig, Petrova, Dessie, Narayan, Shashi, Guez, Arthur, Brahma, Siddhartha, Landon, Jessica, Patel, Miteyan, Zhao, Ruizhe, Villela, Kevin, Wang, Luyu, Jia, Wenhao, Rahtz, Matthew, Giménez, Mai, Yeung, Legg, Keeling, James, Georgiev, Petko, Mincu, Diana, Wu, Boxi, Haykal, Salem, Saputro, Rachel, Vodrahalli, Kiran, Qin, James, Cankara, Zeynep, Sharma, Abhanshu, Fernando, Nick, Hawkins, Will, Neyshabur, Behnam, Kim, Solomon, Hutter, Adrian, Agrawal, Priyanka, Castro-Ros, Alex, Driessche, George van den, Wang, Tao, Yang, Fan, Chang, Shuo-yiin, Komarek, Paul, McIlroy, Ross, Lučić, Mario, Zhang, Guodong, Farhan, Wael, Sharman, Michael, Natsev, Paul, Michel, Paul, Bansal, Yamini, Qiao, Siyuan, Cao, Kris, Shakeri, Siamak, Butterfield, Christina, Chung, Justin, Rubenstein, Paul Kishan, Agrawal, Shivani, Mensch, Arthur, Soparkar, Kedar, Lenc, Karel, Chung, Timothy, Pope, Aedan, Maggiore, Loren, Kay, Jackie, Jhakra, Priya, Wang, Shibo, Maynez, Joshua, Phuong, Mary, Tobin, Taylor, Tacchetti, Andrea, Trebacz, Maja, Robinson, Kevin, Katariya, Yash, Riedel, Sebastian, Bailey, Paige, Xiao, Kefan, Ghelani, Nimesh, Aroyo, Lora, Slone, Ambrose, Houlsby, Neil, Xiong, Xuehan, Yang, Zhen, Gribovskaya, Elena, Adler, Jonas, Wirth, Mateo, Lee, Lisa, Li, Music, Kagohara, Thais, Pavagadhi, Jay, Bridgers, Sophie, Bortsova, Anna, Ghemawat, Sanjay, Ahmed, Zafarali, Liu, Tianqi, Powell, Richard, Bolina, Vijay, Iinuma, Mariko, Zablotskaia, Polina, Besley, James, Chung, Da-Woon, Dozat, Timothy, Comanescu, Ramona, Si, Xiance, Greer, Jeremy, Su, Guolong, Polacek, Martin, Kaufman, Raphaël Lopez, Tokumine, Simon, Hu, Hexiang, Buchatskaya, Elena, Miao, Yingjie, Elhawaty, Mohamed, Siddhant, Aditya, Tomasev, Nenad, Xing, Jinwei, Greer, Christina, Miller, Helen, Ashraf, Shereen, Roy, Aurko, Zhang, Zizhao, Ma, Ada, Filos, Angelos, Besta, Milos, Blevins, Rory, Klimenko, Ted, Yeh, Chih-Kuan, Changpinyo, Soravit, Mu, Jiaqi, Chang, Oscar, Pajarskas, Mantas, Muir, Carrie, Cohen, Vered, Lan, Charline Le, Haridasan, Krishna, Marathe, Amit, Hansen, Steven, Douglas, Sholto, Samuel, Rajkumar, Wang, Mingqiu, Austin, Sophia, Lan, Chang, Jiang, Jiepu, Chiu, Justin, Lorenzo, Jaime Alonso, Sjösund, Lars Lowe, Cevey, Sébastien, Gleicher, Zach, Avrahami, Thi, Boral, Anudhyan, Srinivasan, Hansa, Selo, Vittorio, May, Rhys, Aisopos, Konstantinos, Hussenot, Léonard, Soares, Livio Baldini, Baumli, Kate, Chang, Michael B., Recasens, Adrià, Caine, Ben, Pritzel, Alexander, Pavetic, Filip, Pardo, Fabio, Gergely, Anita, Frye, Justin, Ramasesh, Vinay, Horgan, Dan, Badola, Kartikeya, Kassner, Nora, Roy, Subhrajit, Dyer, Ethan, Campos, Víctor Campos, Tomala, Alex, Tang, Yunhao, Badawy, Dalia El, White, Elspeth, Mustafa, Basil, Lang, Oran, Jindal, Abhishek, Vikram, Sharad, Gong, Zhitao, Caelles, Sergi, Hemsley, Ross, Thornton, Gregory, Feng, Fangxiaoyu, Stokowiec, Wojciech, Zheng, Ce, Thacker, Phoebe, Ünlü, Çağlar, Zhang, Zhishuai, Saleh, Mohammad, Svensson, James, Bileschi, Max, Patil, Piyush, Anand, Ankesh, Ring, Roman, Tsihlas, Katerina, Vezer, Arpi, Selvi, Marco, Shevlane, Toby, Rodriguez, Mikel, Kwiatkowski, Tom, Daruki, Samira, Rong, Keran, Dafoe, Allan, FitzGerald, Nicholas, Gu-Lemberg, Keren, Khan, Mina, Hendricks, Lisa Anne, Pellat, Marie, Feinberg, Vladimir, Cobon-Kerr, James, Sainath, Tara, Rauh, Maribeth, Hashemi, Sayed Hadi, Ives, Richard, Hasson, Yana, Noland, Eric, Cao, Yuan, Byrd, Nathan, Hou, Le, Wang, Qingze, Sottiaux, Thibault, Paganini, Michela, Lespiau, Jean-Baptiste, Moufarek, Alexandre, Hassan, Samer, Shivakumar, Kaushik, van Amersfoort, Joost, Mandhane, Amol, Joshi, Pratik, Goyal, Anirudh, Tung, Matthew, Brock, Andrew, Sheahan, Hannah, Misra, Vedant, Li, Cheng, Rakićević, Nemanja, Dehghani, Mostafa, Liu, Fangyu, Mittal, Sid, Oh, Junhyuk, Noury, Seb, Sezener, Eren, Huot, Fantine, Lamm, Matthew, De Cao, Nicola, Chen, Charlie, Mudgal, Sidharth, Stella, Romina, Brooks, Kevin, Vasudevan, Gautam, Liu, Chenxi, Chain, Mainak, Melinkeri, Nivedita, Cohen, Aaron, Wang, Venus, Seymore, Kristie, Zubkov, Sergey, Goel, Rahul, Yue, Summer, Krishnakumaran, Sai, Albert, Brian, Hurley, Nate, Sano, Motoki, Mohananey, Anhad, Joughin, Jonah, Filonov, Egor, Kępa, Tomasz, Eldawy, Yomna, Lim, Jiawern, Rishi, Rahul, Badiezadegan, Shirin, Bos, Taylor, Chang, Jerry, Jain, Sanil, Padmanabhan, Sri Gayatri Sundara, Puttagunta, Subha, Krishna, Kalpesh, Baker, Leslie, Kalb, Norbert, Bedapudi, Vamsi, Kurzrok, Adam, Lei, Shuntong, Yu, Anthony, Litvin, Oren, Zhou, Xiang, Wu, Zhichun, Sobell, Sam, Siciliano, Andrea, Papir, Alan, Neale, Robby, Bragagnolo, Jonas, Toor, Tej, Chen, Tina, Anklin, Valentin, Wang, Feiran, Feng, Richie, Gholami, Milad, Ling, Kevin, Liu, Lijuan, Walter, Jules, Moghaddam, Hamid, Kishore, Arun, Adamek, Jakub, Mercado, Tyler, Mallinson, Jonathan, Wandekar, Siddhinita, Cagle, Stephen, Ofek, Eran, Garrido, Guillermo, Lombriser, Clemens, Mukha, Maksim, Sun, Botu, Mohammad, Hafeezul Rahman, Matak, Josip, Qian, Yadi, Peswani, Vikas, Janus, Pawel, Yuan, Quan, Schelin, Leif, David, Oana, Garg, Ankur, He, Yifan, Duzhyi, Oleksii, Älgmyr, Anton, Lottaz, Timothée, Li, Qi, Yadav, Vikas, Xu, Luyao, Chinien, Alex, Shivanna, Rakesh, Chuklin, Aleksandr, Li, Josie, Spadine, Carrie, Wolfe, Travis, Mohamed, Kareem, Das, Subhabrata, Dai, Zihang, He, Kyle, von Dincklage, Daniel, Upadhyay, Shyam, Maurya, Akanksha, Chi, Luyan, Krause, Sebastian, Salama, Khalid, Rabinovitch, Pam G, M, Pavan Kumar Reddy, Selvan, Aarush, Dektiarev, Mikhail, Ghiasi, Golnaz, Guven, Erdem, Gupta, Himanshu, Liu, Boyi, Sharma, Deepak, Shtacher, Idan Heimlich, Paul, Shachi, Akerlund, Oscar, Aubet, François-Xavier, Huang, Terry, Zhu, Chen, Zhu, Eric, Teixeira, Elico, Fritze, Matthew, Bertolini, Francesco, Marinescu, Liana-Eleonora, Bölle, Martin, Paulus, Dominik, Gupta, Khyatti, Latkar, Tejasi, Chang, Max, Sanders, Jason, Wilson, Roopa, Wu, Xuewei, Tan, Yi-Xuan, Thiet, Lam Nguyen, Doshi, Tulsee, Lall, Sid, Mishra, Swaroop, Chen, Wanming, Luong, Thang, Benjamin, Seth, Lee, Jasmine, Andrejczuk, Ewa, Rabiej, Dominik, Ranjan, Vipul, Styrc, Krzysztof, Yin, Pengcheng, Simon, Jon, Harriott, Malcolm Rose, Bansal, Mudit, 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Zifan, Hoffmann, John Eric, Lai, Jonathan, Chung, Raynald, Yang, Kai, Balani, Nihal, Bražinskas, Arthur, Sozanschi, Andrei, Hayes, Matthew, Alcalde, Héctor Fernández, Makarov, Peter, Chen, Will, Stella, Antonio, Snijders, Liselotte, Mandl, Michael, Kärrman, Ante, Nowak, Paweł, Wu, Xinyi, Dyck, Alex, Vaidyanathan, Krishnan, R, Raghavender, Mallet, Jessica, Rudominer, Mitch, Johnston, Eric, Mittal, Sushil, Udathu, Akhil, Christensen, Janara, Verma, Vishal, Irving, Zach, Santucci, Andreas, Elsayed, Gamaleldin, Davoodi, Elnaz, Georgiev, Marin, Tenney, Ian, Hua, Nan, Cideron, Geoffrey, Leurent, Edouard, Alnahlawi, Mahmoud, Georgescu, Ionut, Wei, Nan, Zheng, Ivy, Scandinaro, Dylan, Jiang, Heinrich, Snoek, Jasper, Sundararajan, Mukund, Wang, Xuezhi, Ontiveros, Zack, Karo, Itay, Cole, Jeremy, Rajashekhar, Vinu, Tumeh, Lara, Ben-David, Eyal, Jain, Rishub, Uesato, Jonathan, Datta, Romina, Bunyan, Oskar, Wu, Shimu, Zhang, John, Stanczyk, Piotr, Zhang, Ye, Steiner, David, Naskar, Subhajit, Azzam, Michael, Johnson, Matthew, Paszke, Adam, Chiu, Chung-Cheng, Elias, Jaume Sanchez, Mohiuddin, Afroz, Muhammad, Faizan, Miao, Jin, Lee, Andrew, Vieillard, Nino, Park, Jane, Zhang, Jiageng, Stanway, Jeff, Garmon, Drew, Karmarkar, Abhijit, Dong, Zhe, Lee, Jong, Kumar, Aviral, Zhou, Luowei, Evens, Jonathan, Isaac, William, Irving, Geoffrey, Loper, Edward, Fink, Michael, Arkatkar, Isha, Chen, Nanxin, Shafran, Izhak, Petrychenko, Ivan, Chen, Zhe, Jia, Johnson, Levskaya, Anselm, Zhu, Zhenkai, Grabowski, Peter, Mao, Yu, Magni, Alberto, Yao, Kaisheng, Snaider, Javier, Casagrande, Norman, Palmer, Evan, Suganthan, Paul, Castaño, Alfonso, Giannoumis, Irene, Kim, Wooyeol, Rybiński, Mikołaj, Sreevatsa, Ashwin, Prendki, Jennifer, Soergel, David, Goedeckemeyer, Adrian, Gierke, Willi, Jafari, Mohsen, Gaba, Meenu, Wiesner, Jeremy, Wright, Diana Gage, Wei, Yawen, Vashisht, Harsha, Kulizhskaya, Yana, Hoover, Jay, Le, Maigo, Li, Lu, Iwuanyanwu, Chimezie, Liu, Lu, Ramirez, Kevin, Khorlin, Andrey, Cui, Albert, LIN, Tian, Wu, Marcus, Aguilar, Ricardo, Pallo, Keith, Chakladar, Abhishek, Perng, Ginger, Abellan, Elena Allica, Zhang, Mingyang, Dasgupta, Ishita, Kushman, Nate, Penchev, Ivo, Repina, Alena, Wu, Xihui, van der Weide, Tom, Ponnapalli, Priya, Kaplan, Caroline, Simsa, Jiri, Li, Shuangfeng, Dousse, Olivier, Piper, Jeff, Ie, Nathan, Pasumarthi, Rama, Lintz, Nathan, Vijayakumar, Anitha, Andor, Daniel, Valenzuela, Pedro, Lui, Minnie, Paduraru, Cosmin, Peng, Daiyi, Lee, Katherine, Zhang, Shuyuan, Greene, Somer, Nguyen, Duc Dung, Kurylowicz, Paula, Hardin, Cassidy, Dixon, Lucas, Janzer, Lili, Choo, Kiam, Feng, Ziqiang, Zhang, Biao, Singhal, Achintya, Du, Dayou, McKinnon, Dan, Antropova, Natasha, Bolukbasi, Tolga, Keller, Orgad, Reid, David, Finchelstein, Daniel, Raad, Maria Abi, Crocker, Remi, Hawkins, Peter, Dadashi, Robert, Gaffney, Colin, Franko, Ken, Bulanova, Anna, Leblond, Rémi, Chung, Shirley, Askham, Harry, Cobo, Luis C., Xu, Kelvin, Fischer, Felix, Xu, Jun, Sorokin, Christina, Alberti, Chris, Lin, Chu-Cheng, Evans, Colin, Dimitriev, Alek, Forbes, Hannah, Banarse, Dylan, Tung, Zora, Omernick, Mark, Bishop, Colton, Sterneck, Rachel, Jain, Rohan, Xia, Jiawei, Amid, Ehsan, Piccinno, Francesco, Wang, Xingyu, Banzal, Praseem, Mankowitz, Daniel J., Polozov, Alex, Krakovna, Victoria, Brown, Sasha, Bateni, MohammadHossein, Duan, Dennis, Firoiu, Vlad, Thotakuri, Meghana, Natan, Tom, Geist, Matthieu, Girgin, Ser tan, Li, Hui, Ye, Jiayu, Roval, Ofir, Tojo, Reiko, Kwong, Michael, Lee-Thorp, James, Yew, Christopher, Sinopalnikov, Danila, Ramos, Sabela, Mellor, John, Sharma, Abhishek, Wu, Kathy, Miller, David, Sonnerat, Nicolas, Vnukov, Denis, Greig, Rory, Beattie, Jennifer, Caveness, Emily, Bai, Libin, Eisenschlos, Julian, Korchemniy, Alex, Tsai, Tomy, Jasarevic, Mimi, Kong, Weize, Dao, Phuong, Zheng, Zeyu, Liu, Frederick, Zhu, Rui, Teh, Tian Huey, Sanmiya, Jason, Gladchenko, Evgeny, Trdin, Nejc, Toyama, Daniel, Rosen, Evan, Tavakkol, Sasan, Xue, Linting, Elkind, Chen, Woodman, Oliver, Carpenter, John, Papamakarios, George, Kemp, Rupert, Kafle, Sushant, Grunina, Tanya, Sinha, Rishika, Talbert, Alice, Wu, Diane, Owusu-Afriyie, Denese, Thornton, Chloe, Pont-Tuset, Jordi, Narayana, Pradyumna, Li, Jing, Fatehi, Saaber, Wieting, John, Ajmeri, Omar, Uria, Benigno, Ko, Yeongil, Knight, Laura, Héliou, Amélie, Niu, Ning, Gu, Shane, Pang, Chenxi, Li, Yeqing, Levine, Nir, Stolovich, Ariel, Santamaria-Fernandez, Rebeca, Goenka, Sonam, Yustalim, Wenny, Strudel, Robin, Elqursh, Ali, Deck, Charlie, Lee, Hyo, Li, Zonglin, Levin, Kyle, Hoffmann, Raphael, Holtmann-Rice, Dan, Bachem, Olivier, Arora, Sho, Koh, Christy, Yeganeh, Soheil Hassas, Põder, Siim, Tariq, Mukarram, Sun, Yanhua, Ionita, Lucian, Seyedhosseini, Mojtaba, Tafti, Pouya, Liu, Zhiyu, Gulati, Anmol, Liu, Jasmine, Ye, Xinyu, Chrzaszcz, Bart, Wang, Lily, Sethi, Nikhil, Li, Tianrun, Brown, Ben, Singh, Shreya, Fan, Wei, Parisi, Aaron, Stanton, Joe, Koverkathu, Vinod, Choquette-Choo, Christopher A., Li, Yunjie, Lu, TJ, Shroff, Prakash, Varadarajan, Mani, Bahargam, Sanaz, Willoughby, Rob, Gaddy, David, Desjardins, Guillaume, Cornero, Marco, Robenek, Brona, Mittal, Bhavishya, Albrecht, Ben, Shenoy, Ashish, Moiseev, Fedor, Jacobsson, Henrik, Ghaffarkhah, Alireza, Rivière, Morgane, Walton, Alanna, Crepy, Clément, Parrish, Alicia, Zhou, Zongwei, Farabet, Clement, Radebaugh, Carey, Srinivasan, Praveen, van der Salm, Claudia, Fidjeland, Andreas, Scellato, Salvatore, Latorre-Chimoto, Eri, Klimczak-Plucińska, Hanna, Bridson, David, de Cesare, Dario, Hudson, Tom, Mendolicchio, Piermaria, Walker, Lexi, Morris, Alex, Mauger, Matthew, Guseynov, Alexey, Reid, Alison, Odoom, Seth, Loher, Lucia, Cotruta, Victor, Yenugula, Madhavi, Grewe, Dominik, Petrushkina, Anastasia, Duerig, Tom, Sanchez, Antonio, Yadlowsky, Steve, Shen, Amy, Globerson, Amir, Webb, Lynette, Dua, Sahil, Li, Dong, Bhupatiraju, Surya, Hurt, Dan, Qureshi, Haroon, Agarwal, Ananth, Shani, Tomer, Eyal, Matan, Khare, Anuj, Belle, Shreyas Rammohan, Wang, Lei, Tekur, Chetan, Kale, Mihir Sanjay, Wei, Jinliang, Sang, Ruoxin, Saeta, Brennan, Liechty, Tyler, Sun, Yi, Zhao, Yao, Lee, Stephan, Nayak, Pandu, Fritz, Doug, Vuyyuru, Manish Reddy, Aslanides, John, Vyas, Nidhi, Wicke, Martin, Ma, Xiao, Eltyshev, Evgenii, Martin, Nina, Cate, Hardie, Manyika, James, Amiri, Keyvan, Kim, Yelin, Xiong, Xi, Kang, Kai, Luisier, Florian, Tripuraneni, Nilesh, Madras, David, Guo, Mandy, Waters, Austin, Wang, Oliver, Ainslie, Joshua, Baldridge, Jason, Zhang, Han, Pruthi, Garima, Bauer, Jakob, Yang, Feng, Mansour, Riham, Gelman, Jason, Xu, Yang, Polovets, George, Liu, Ji, Cai, Honglong, Chen, Warren, Sheng, XiangHai, Xue, Emily, Ozair, Sherjil, Angermueller, Christof, Li, Xiaowei, Sinha, Anoop, Wang, Weiren, Wiesinger, Julia, Koukoumidis, Emmanouil, Tian, Yuan, Iyer, Anand, Gurumurthy, Madhu, Goldenson, Mark, Shah, Parashar, Blake, MK, Yu, Hongkun, Urbanowicz, Anthony, Palomaki, Jennimaria, Fernando, Chrisantha, Durden, Ken, Mehta, Harsh, Momchev, Nikola, Rahimtoroghi, Elahe, Georgaki, Maria, Raul, Amit, Ruder, Sebastian, Redshaw, Morgan, Lee, Jinhyuk, Zhou, Denny, Jalan, Komal, Li, Dinghua, Hechtman, Blake, Schuh, Parker, Nasr, Milad, Milan, Kieran, Mikulik, Vladimir, Franco, Juliana, Green, Tim, Nguyen, Nam, Kelley, Joe, Mahendru, Aroma, Hu, Andrea, Howland, Joshua, Vargas, Ben, Hui, Jeffrey, Bansal, Kshitij, Rao, Vikram, Ghiya, Rakesh, Wang, Emma, Ye, Ke, Sarr, Jean Michel, Preston, Melanie Moranski, Elish, Madeleine, Li, Steve, Kaku, Aakash, Gupta, Jigar, Pasupat, Ice, Juan, Da-Cheng, Someswar, Milan, M., Tejvi, Chen, Xinyun, Amini, Aida, Fabrikant, Alex, Chu, Eric, Dong, Xuanyi, Muthal, Amruta, Buthpitiya, Senaka, Jauhari, Sarthak, Khandelwal, Urvashi, Hitron, Ayal, Ren, Jie, Rinaldi, Larissa, Drath, Shahar, Dabush, Avigail, Jiang, Nan-Jiang, Godhia, Harshal, Sachs, Uli, Chen, Anthony, Fan, Yicheng, Taitelbaum, Hagai, Noga, Hila, Dai, Zhuyun, Wang, James, Hamer, Jenny, Ferng, Chun-Sung, Elkind, Chenel, Atias, Aviel, Lee, Paulina, Listík, Vít, Carlen, Mathias, van de Kerkhof, Jan, Pikus, Marcin, Zaher, Krunoslav, Müller, Paul, Zykova, Sasha, Stefanec, Richard, Gatsko, Vitaly, Hirnschall, Christoph, Sethi, Ashwin, Xu, Xingyu Federico, Ahuja, Chetan, Tsai, Beth, Stefanoiu, Anca, Feng, Bo, Dhandhania, Keshav, Katyal, Manish, Gupta, Akshay, Parulekar, Atharva, Pitta, Divya, Zhao, Jing, Bhatia, Vivaan, Bhavnani, Yashodha, Alhadlaq, Omar, Li, Xiaolin, Danenberg, Peter, Tu, Dennis, Pine, Alex, Filippova, Vera, Ghosh, Abhipso, Limonchik, Ben, Urala, Bhargava, Lanka, Chaitanya Krishna, Clive, Derik, Li, Edward, Wu, Hao, Hongtongsak, Kevin, Li, Ianna, Thakkar, Kalind, Omarov, Kuanysh, Majmundar, Kushal, Alverson, Michael, Kucharski, Michael, Patel, Mohak, Jain, Mudit, Zabelin, Maksim, Pelagatti, Paolo, Kohli, Rohan, Kumar, Saurabh, Kim, Joseph, Sankar, Swetha, Shah, Vineet, Ramachandruni, Lakshmi, Zeng, Xiangkai, Bariach, Ben, Weidinger, Laura, Vu, Tu, Subramanya, Amar, Hsiao, Sissie, Hassabis, Demis, Kavukcuoglu, Koray, Sadovsky, Adam, Le, Quoc, Strohman, Trevor, Wu, Yonghui, Petrov, Slav, Dean, Jeffrey, and Vinyals, Oriol
Abstract: This report introduces a new family of multimodal models, Gemini, that exhibit remarkable capabilities across image, audio, video, and text understanding. The Gemini family consists of Ultra, Pro, and Nano sizes, suitable for applications ranging from complex reasoning tasks to on-device memory-constrained use-cases. Evaluation on a broad range of benchmarks shows that our most-capable Gemini Ultra model advances the state of the art in 30 of 32 of these benchmarks - notably being the first model to achieve human-expert performance on the well-studied exam benchmark MMLU, and improving the state of the art in every one of the 20 multimodal benchmarks we examined. We believe that the new capabilities of the Gemini family in cross-modal reasoning and language understanding will enable a wide variety of use cases. We discuss our approach toward post-training and deploying Gemini models responsibly to users through services including Gemini, Gemini Advanced, Google AI Studio, and Cloud Vertex AI.
Published: 2023

38. Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search

Author: Mehrabian, Abbas, Anand, Ankit, Kim, Hyunjik, Sonnerat, Nicolas, Balog, Matej, Comanici, Gheorghe, Berariu, Tudor, Lee, Andrew, Ruoss, Anian, Bulanova, Anna, Toyama, Daniel, Blackwell, Sam, Paredes, Bernardino Romera, Veličković, Petar, Orseau, Laurent, Lee, Joonkyung, Naredla, Anurag Murty, Precup, Doina, Wagner, Adam Zsolt, Mehrabian, Abbas, Anand, Ankit, Kim, Hyunjik, Sonnerat, Nicolas, Balog, Matej, Comanici, Gheorghe, Berariu, Tudor, Lee, Andrew, Ruoss, Anian, Bulanova, Anna, Toyama, Daniel, Blackwell, Sam, Paredes, Bernardino Romera, Veličković, Petar, Orseau, Laurent, Lee, Joonkyung, Naredla, Anurag Murty, Precup, Doina, and Wagner, Adam Zsolt
Abstract: This work studies a central extremal graph theory problem inspired by a 1975 conjecture of Erd\H{o}s, which aims to find graphs with a given size (number of nodes) that maximize the number of edges without having 3- or 4-cycles. We formulate this problem as a sequential decision-making problem and compare AlphaZero, a neural network-guided tree search, with tabu search, a heuristic local search method. Using either method, by introducing a curriculum -- jump-starting the search for larger graphs using good graphs found at smaller sizes -- we improve the state-of-the-art lower bounds for several sizes. We also propose a flexible graph-generation environment and a permutation-invariant network architecture for learning to search in the space of graphs., Comment: Accepted at MATH AI workshop at NeurIPS 2023, First three authors contributed equally, Last two authors have equal senior contribution
Published: 2023

39. Timbre-Trap: A Low-Resource Framework for Instrument-Agnostic Music Transcription

Author: Cwitkowitz, Frank, Cheuk, Kin Wai, Choi, Woosung, Martínez-Ramírez, Marco A., Toyama, Keisuke, Liao, Wei-Hsiang, Mitsufuji, Yuki, Cwitkowitz, Frank, Cheuk, Kin Wai, Choi, Woosung, Martínez-Ramírez, Marco A., Toyama, Keisuke, Liao, Wei-Hsiang, and Mitsufuji, Yuki
Abstract: In recent years, research on music transcription has focused mainly on architecture design and instrument-specific data acquisition. With the lack of availability of diverse datasets, progress is often limited to solo-instrument tasks such as piano transcription. Several works have explored multi-instrument transcription as a means to bolster the performance of models on low-resource tasks, but these methods face the same data availability issues. We propose Timbre-Trap, a novel framework which unifies music transcription and audio reconstruction by exploiting the strong separability between pitch and timbre. We train a single autoencoder to simultaneously estimate pitch salience and reconstruct complex spectral coefficients, selecting between either output during the decoding stage via a simple switch mechanism. In this way, the model learns to produce coefficients corresponding to timbre-less audio, which can be interpreted as pitch salience. We demonstrate that the framework leads to performance comparable to state-of-the-art instrument-agnostic transcription methods, while only requiring a small amount of annotated data., Comment: Accepted to ICASSP 2024
Published: 2023

40. AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning

Author: Mathieu, Michaël, Ozair, Sherjil, Srinivasan, Srivatsan, Gulcehre, Caglar, Zhang, Shangtong, Jiang, Ray, Paine, Tom Le, Powell, Richard, Żołna, Konrad, Schrittwieser, Julian, Choi, David, Georgiev, Petko, Toyama, Daniel, Huang, Aja, Ring, Roman, Babuschkin, Igor, Ewalds, Timo, Bordbar, Mahyar, Henderson, Sarah, Colmenarejo, Sergio Gómez, Oord, Aäron van den, Czarnecki, Wojciech Marian, de Freitas, Nando, Vinyals, Oriol, Mathieu, Michaël, Ozair, Sherjil, Srinivasan, Srivatsan, Gulcehre, Caglar, Zhang, Shangtong, Jiang, Ray, Paine, Tom Le, Powell, Richard, Żołna, Konrad, Schrittwieser, Julian, Choi, David, Georgiev, Petko, Toyama, Daniel, Huang, Aja, Ring, Roman, Babuschkin, Igor, Ewalds, Timo, Bordbar, Mahyar, Henderson, Sarah, Colmenarejo, Sergio Gómez, Oord, Aäron van den, Czarnecki, Wojciech Marian, de Freitas, Nando, and Vinyals, Oriol
Abstract: StarCraft II is one of the most challenging simulated reinforcement learning environments; it is partially observable, stochastic, multi-agent, and mastering StarCraft II requires strategic planning over long time horizons with real-time low-level execution. It also has an active professional competitive scene. StarCraft II is uniquely suited for advancing offline RL algorithms, both because of its challenging nature and because Blizzard has released a massive dataset of millions of StarCraft II games played by human players. This paper leverages that and establishes a benchmark, called AlphaStar Unplugged, introducing unprecedented challenges for offline reinforcement learning. We define a dataset (a subset of Blizzard's release), tools standardizing an API for machine learning methods, and an evaluation protocol. We also present baseline agents, including behavior cloning, offline variants of actor-critic and MuZero. We improve the state of the art of agents using only offline data, and we achieve 90% win rate against previously published AlphaStar behavior cloning agent., Comment: 32 pages, 13 figures, previous version published as a NeurIPS 2021 workshop: https://openreview.net/forum?id=Np8Pumfoty
Published: 2023

41. Automatic Piano Transcription with Hierarchical Frequency-Time Transformer

Author: Toyama, Keisuke, Akama, Taketo, Ikemiya, Yukara, Takida, Yuhta, Liao, Wei-Hsiang, Mitsufuji, Yuki, Toyama, Keisuke, Akama, Taketo, Ikemiya, Yukara, Takida, Yuhta, Liao, Wei-Hsiang, and Mitsufuji, Yuki
Abstract: Taking long-term spectral and temporal dependencies into account is essential for automatic piano transcription. This is especially helpful when determining the precise onset and offset for each note in the polyphonic piano content. In this case, we may rely on the capability of self-attention mechanism in Transformers to capture these long-term dependencies in the frequency and time axes. In this work, we propose hFT-Transformer, which is an automatic music transcription method that uses a two-level hierarchical frequency-time Transformer architecture. The first hierarchy includes a convolutional block in the time axis, a Transformer encoder in the frequency axis, and a Transformer decoder that converts the dimension in the frequency axis. The output is then fed into the second hierarchy which consists of another Transformer encoder in the time axis. We evaluated our method with the widely used MAPS and MAESTRO v3.0.0 datasets, and it demonstrated state-of-the-art performance on all the F1-scores of the metrics among Frame, Note, Note with Offset, and Note with Offset and Velocity estimations., Comment: 8 pages, 6 figures, to be published in ISMIR2023
Published: 2023

42. Tracheostomy decannulation rates in Japan: a retrospective cohort study using a claims database

Author: 40450598, 70217933, Ishizaki, Miho, Toyama, Mayumi, Imura, Haruki, Takahashi, Yoshimitsu, Nakayama, Takeo, 40450598, 70217933, Ishizaki, Miho, Toyama, Mayumi, Imura, Haruki, Takahashi, Yoshimitsu, and Nakayama, Takeo
Abstract: Despite the exponential increase in the use of tracheostomy worldwide, rates of tracheostomy decannulation are unknown. We conducted a retrospective cohort study to investigate tracheostomy decannulation rates among adult patients over a two-year period and explored factors associated with prolonged tracheostomy. A health insurance claims database including 3, 758, 210 people in Japan was used. The primary outcome was time to decannulation. Assessed patient and hospital factors included age, sex, emergency endotracheal intubation, disease, and hospital size. A total of 917 patients underwent tracheostomy, and 752 met the eligibility criteria. Decannulation rates were 40.8% (95% confidence interval 36.8-44.9) at 3 months, 63.9% (58.4-69.0) at 12 months, and 65.0% (59.2-70.3) at 24 months. Hazard ratios of patient and hospital factors for tracheostomy decannulation were 0.44 for age (65-74 years) (95% confidence interval 0.28-0.68), 0.81 (0.63-1.05) for female sex, and 0.59 (0.45-0.76) for emergency endotracheal intubation. Cerebrovascular disease, head injuries, and cardiac arrest had lower hazard ratios compared to other diseases. Decannulation rates among adult patients in Japan increased rapidly up to 3 months after tracheostomy, reaching a plateau after 12 months. Older age, female sex, emergency endotracheal intubation, cerebrovascular disease, head injuries, and cardiac arrest were associated with prolonged tracheostomy.
Published: 2022

43. On power series generated by simpler sequences and having strong algebraic independence properties (Analytic Number Theory and Related Topics)

Author: Tanaka, Taka-aki, Toyama, Kento, Tanaka, Taka-aki, and Toyama, Kento
Published: 2022

44. This title is unavailable for guests, please login to see more information.

Author: 20750368, Suzuki, K N, Gogami, T, Pandey, B, Itabashi, K, Nagao, S, Okuyama, K, Nakamura, S N, Tang, L, Abrams, D, Akiyama, T, Androic, D, Aniol, K, Gayoso, C Ayerbe, Bane, J, Barcus, S, Barrow, J, Bellini, V, Bhatt, H, Bhetuwal, D, Biswas, D, Camsonne, A, Castellanos, J, Chen, J-P, Chen, J, Covrig, S, Chrisman, D, Cruz-Torres, R, Das, R, Fuchey, E, Gnanvo, K, Garibaldi, F, Gautam, T, Gomez, J, Gueye, P, Hague, T J, Hansen, O, Henry, W, Hauenstein, F, Higinbotham, D W, Hyde, C E, Kaneta, M, Keppel, C, Kutz, T, Lashley-Colthirst, N, Li, S, Liu, H, Mammei, J, Markowitz, P, McClellan, R E, Meddi, F, Meekins, D, Michaels, R, Mihovilovič, M, Moyer, A, Nguyen, D, Nycz, M, Owen, V, Palatchi, C, Park, S, Petkovic, T, Premathilake, S, Reimer, P E, Reinhold, J, Riordan, S, Rodriguez, V, Samanta, C, Santiesteban, S N, Sawatzky, B, Širca, S, Slifer, K, Su, T, Tian, Y, Toyama, Y, Uehara, K, Urciuoli, G M, Votaw, D, Williamson, J, Wojtsekhowski, B, Wood, S A, Yale, B, Ye, Z, Zhang, J, Zheng, X, 20750368, Suzuki, K N, Gogami, T, Pandey, B, Itabashi, K, Nagao, S, Okuyama, K, Nakamura, S N, Tang, L, Abrams, D, Akiyama, T, Androic, D, Aniol, K, Gayoso, C Ayerbe, Bane, J, Barcus, S, Barrow, J, Bellini, V, Bhatt, H, Bhetuwal, D, Biswas, D, Camsonne, A, Castellanos, J, Chen, J-P, Chen, J, Covrig, S, Chrisman, D, Cruz-Torres, R, Das, R, Fuchey, E, Gnanvo, K, Garibaldi, F, Gautam, T, Gomez, J, Gueye, P, Hague, T J, Hansen, O, Henry, W, Hauenstein, F, Higinbotham, D W, Hyde, C E, Kaneta, M, Keppel, C, Kutz, T, Lashley-Colthirst, N, Li, S, Liu, H, Mammei, J, Markowitz, P, McClellan, R E, Meddi, F, Meekins, D, Michaels, R, Mihovilovič, M, Moyer, A, Nguyen, D, Nycz, M, Owen, V, Palatchi, C, Park, S, Petkovic, T, Premathilake, S, Reimer, P E, Reinhold, J, Riordan, S, Rodriguez, V, Samanta, C, Santiesteban, S N, Sawatzky, B, Širca, S, Slifer, K, Su, T, Tian, Y, Toyama, Y, Uehara, K, Urciuoli, G M, Votaw, D, Williamson, J, Wojtsekhowski, B, Wood, S A, Yale, B, Ye, Z, Zhang, J, and Zheng, X
Published: 2022

45. Growth Promotion of Giant Duckweed Spirodela polyrhiza (Lemnaceae) by Ensifer sp. SP4 Through Enhancement of Nitrogen Metabolism and Photosynthesis

Author: Toyama, Tadashi, Mori, Kazuhiro, Tanaka, Yasuhiro, Ike, Michihiko, Morikawa, Masaaki, Toyama, Tadashi, Mori, Kazuhiro, Tanaka, Yasuhiro, Ike, Michihiko, and Morikawa, Masaaki
Abstract: Duckweeds (Lemnaceae) are representative producers in fresh aquatic ecosystems and also yield sustainable biomass for animal feeds, human foods, and biofuels, and contribute toward effective wastewater treatment; thus, enhancing duckweed productivity is a critical challenge. Plant-growth -promoting bacteria (PGPB) can improve the productivity of terrestrial plants; however, duckweed-PGPB interactions remain unclear and no previous study has investigated the molecular mechanisms underlying duckweed-PGPB interaction. Herein, a PGPB, Ensifer sp. strain SP4, was newly isolated from giant duckweed (Spirodela polyrhiza), and the interactions between S. polyrhiza and SP4 were investigated through physiological, biochemical, and metabolomic analyses. In S. polyrhiza and SP4 coculture, SP4 increased the nitrogen (N), chlorophyll, and ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) contents and the photosynthesis rate of S. polyrhiza by 2.5-, 2.5-, 2.7-, and 2.4-fold, respectively. Elevated photosynthesis increased the relative growth rate and biomass productivity of S. polyrhiza by 1.5 and 2.7-fold, respectively. Strain SP4 significantly altered the metabolomic profile of S. polyrhiza, especially its amino acid profile. N stable isotope analysis revealed that organic N compounds were transferred from SP4 to S. polyrhiza. These N compounds, particularly glutamic acid, possibly triggered the increase in photosynthetic and growth activities. Accordingly, we propose a new model for the molecular mechanism underlying S. polyrhiza growth promotion by its associated bacteria Ensifer sp. SP4, which occurs through enhanced N compound metabolism and photosynthesis. Our findings show that Ensifer sp. SP4 is a promising PGPB for increasing biomass yield, wastewater purification activity, and CO2 capture of S. polyrhiza.
Published: 2022

46. Implementation of design based learning for the development of SDGs educational games

Author: Maharjan, Namita, Kuroda, Kyohei, Silwal, Gunjan, Toyama, Shigehiro, Ominato, Yoshihiro, Tsuchida, Yasuko, Araki, Nobuo, Yamaguchi, Takashi, Ichitsubo, Makoto, Maharjan, Namita, Kuroda, Kyohei, Silwal, Gunjan, Toyama, Shigehiro, Ominato, Yoshihiro, Tsuchida, Yasuko, Araki, Nobuo, Yamaguchi, Takashi, and Ichitsubo, Makoto
Abstract: Education on sustainable education (ESD) is gaining momentum to ensure that SDGs are met by 2030. The educational institutions have significant role in fostering ESD. However, there is lack of educational resources to be used for ESD. Particularly, teaching the concept of SDGs needs an attention grabbing and engaging approach and Design Based Learning (DBL) holds much potential. The main objective of this investigation was to describe the development of SDGs education resources i.e., SDGs educational games using DBL approach. Besides, the generic skills of the students during DBL were assessed during game development phase. The outputs of DBL were Bingo Mat game, Carrom board game and Sugoroku game. These games were validated for their effectiveness as resource for teaching and learning SDGs. The results revealed the positive impact on the generic skills of students through DBL during game development phase. Moreover, the response results of the players highlighted that carrom board game offered them the gaming experience while Bingo and Sugoroku offered them learning experience. Another important finding of this study is the need to teach SDGs from the younger age as the level of education had significantly impacted on their knowledge about SDGs. The results of this study will contribute to the domain of ESD by articulating an alternative pedagogy of integrating DBL with SDGs as invigorating educational resources and faculty development method.
Published: 2022

47. Mutual complementarity among diverse pollinators as a mechanism underlying open insect pollination in Japanese pear orchards

Author: Sonoda Shoji, Kagawa Kiyohiko, Furui Yuki, Nakada Ken, Koyama Mitsuko, Toda Seishi, Sugiura Naoyuki, Nakamura Shoko, Sueyoshi Masahiro, Mita Toshiharu, Toyama Masatoshi, Sonoda Shoji, Kagawa Kiyohiko, Furui Yuki, Nakada Ken, Koyama Mitsuko, Toda Seishi, Sugiura Naoyuki, Nakamura Shoko, Sueyoshi Masahiro, Mita Toshiharu, and Toyama Masatoshi
Published: 2022

48. Development of a Compact Divertor Plasma Simulator for Plasma-Wall Interaction Studies on Neutron-Irradiated Materials

Author: OHNO, Noriyasu, KUWABARA, Tatsuya, TAKAGI, Makoto, NISHIMURA, Ryo, YAJIMA, Miyuki, SAGARA, Akio, TOYAMA, Takeshi, SUZUKI, Katuya, KURISHITA, Hiroaki, SHIKAMA, Tatsuo, HATANO, Yuji, YOSHIDA, Naoaki, OHNO, Noriyasu, KUWABARA, Tatsuya, TAKAGI, Makoto, NISHIMURA, Ryo, YAJIMA, Miyuki, SAGARA, Akio, TOYAMA, Takeshi, SUZUKI, Katuya, KURISHITA, Hiroaki, SHIKAMA, Tatsuo, HATANO, Yuji, and YOSHIDA, Naoaki
Abstract: We have developed a compact divertor plasma simulator (CDPS) that can produce steady-state deuterium and/or helium plasmas with densities above ∼ 1018 m−3 for Plasma-Wall Interaction (PWI) studies of neutron-irradiated materials. The maximum particle flux is about 1022 m−2s−1. The CDPS was installed and is being operated in the radiation-controlled area of the International Research Center for Nuclear Materials Science, Institute for Materials Research, Tohoku University. We are able to control sample temperature within uncertainty of 5 °C during plasma exposure by adjusting the cooling air flow rate to the sample holder. The CDPS has a sample-carrier system, which makes it possible to transfer a plasma-irradiated sample from the sample holder to an infrared heater for analysis using thermal desorption spectroscopy (TDS) without exposing it to the air. This avoids the oxidation of the sample and minimizes the time between the end of plasma exposure and TDS analysis. An ITER-like tungsten (W) sample (A.L.M.T. Corp.), which has been irradiated by neutrons to 0.06 dpa in a fission reactor, was exposed to a deuterium plasma in the CDPS. The experimental results clearly show that the total deuterium retention in the neutron-irradiated W sample increases significantly in comparison with a pristine W, as demonstrated by broadening of the TDS spectrum at high temperatures., source:https://doi.org/10.1585/pfr.12.1405040, identifier:0000-0001-7826-0046
Published: 2022

49. Dynamics of Hydrogen Isotope Absorption and Emission of Neutron-Irradiated Tungsten

Author: TOYAMA, Takeshi, YAJIMA, Miyuki, OHNO, Noriyasu, KUWABARA, Tatsuya, ALIMOV, Vladimir Kh., HATANO, Yuji, TOYAMA, Takeshi, YAJIMA, Miyuki, OHNO, Noriyasu, KUWABARA, Tatsuya, ALIMOV, Vladimir Kh., and HATANO, Yuji
Abstract: This overview presents recent results regarding hydrogen isotope absorption and emission dynamics in neutron-irradiated tungsten (W) using our recently developed Compact Diverter Plasma Simulator (CDPS), a linear plasma device in a radiation-controlled area. Neutron irradiation to 0.016 - 0.06 displacement per atom resulted in a significant increase in deuterium (D) retention due to trapping effects of radiation-induced defects. We analyzed the dependency of D retention on the D plasma fluence by exposing neutron-irradiated pure W to D plasma at 563 K over a range of D fluence values. The total retention was revealed to be proportional to the square root of D fluence, indicating that the implanted D atoms first occupy the defects caused by neutron-irradiation near the surface and then the defects located in deeper regions. We further investigated the effects of post-plasma annealing on D emission; neutron-irradiated pure W was exposed to D plasma at 573 K and was then annealed at the same temperature for 30 hours. Approximately 10% of the absorbed D was released by annealing, suggesting that a heat treatment of the plasma-facing component of a fusion reactor at moderately elevated temperatures could contribute to the removal of accumulated hydrogen isotopes. The experimental results obtained in this study were only available by investigating neutron-irradiated specimens with the CDPS system, which will be essential for future studies of material behavior and plasma-wall interactions in the fusion reactor environment., source:https://doi.org/10.1585/pfr.15.1505081
Published: 2022

50. Growth Promotion of Giant Duckweed Spirodela polyrhiza (Lemnaceae) by Ensifer sp. SP4 Through Enhancement of Nitrogen Metabolism and Photosynthesis

Author: 1000060431392, Toyama, Tadashi, 1000090294040, Mori, Kazuhiro, 1000050377587, Tanaka, Yasuhiro, 1000040222856, Ike, Michihiko, 1000020230104, Morikawa, Masaaki, 1000060431392, Toyama, Tadashi, 1000090294040, Mori, Kazuhiro, 1000050377587, Tanaka, Yasuhiro, 1000040222856, Ike, Michihiko, 1000020230104, and Morikawa, Masaaki
Abstract: Duckweeds (Lemnaceae) are representative producers in fresh aquatic ecosystems and also yield sustainable biomass for animal feeds, human foods, and biofuels, and contribute toward effective wastewater treatment; thus, enhancing duckweed productivity is a critical challenge. Plant-growth -promoting bacteria (PGPB) can improve the productivity of terrestrial plants; however, duckweed-PGPB interactions remain unclear and no previous study has investigated the molecular mechanisms underlying duckweed-PGPB interaction. Herein, a PGPB, Ensifer sp. strain SP4, was newly isolated from giant duckweed (Spirodela polyrhiza), and the interactions between S. polyrhiza and SP4 were investigated through physiological, biochemical, and metabolomic analyses. In S. polyrhiza and SP4 coculture, SP4 increased the nitrogen (N), chlorophyll, and ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) contents and the photosynthesis rate of S. polyrhiza by 2.5-, 2.5-, 2.7-, and 2.4-fold, respectively. Elevated photosynthesis increased the relative growth rate and biomass productivity of S. polyrhiza by 1.5 and 2.7-fold, respectively. Strain SP4 significantly altered the metabolomic profile of S. polyrhiza, especially its amino acid profile. N stable isotope analysis revealed that organic N compounds were transferred from SP4 to S. polyrhiza. These N compounds, particularly glutamic acid, possibly triggered the increase in photosynthetic and growth activities. Accordingly, we propose a new model for the molecular mechanism underlying S. polyrhiza growth promotion by its associated bacteria Ensifer sp. SP4, which occurs through enhanced N compound metabolism and photosynthesis. Our findings show that Ensifer sp. SP4 is a promising PGPB for increasing biomass yield, wastewater purification activity, and CO2 capture of S. polyrhiza.
Published: 2022

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