Author: "Boral, A" - Searchworks@Jio Institute Digital Library Search Results

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2,073 results on '"Boral, A"'

1. ACEV: Unsupervised Intersecting Manifold Segmentation using Adaptation to Angular Change of Eigenvectors in Intrinsic Dimension

Author: Boral, Subhadip, Pal, Rikathi, and Ghosh, Ashish
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Computational Geometry
Abstract: Intersecting manifold segmentation has been a focus of research, where individual manifolds, that intersect with other manifolds, are separated to discover their distinct properties. The proposed method is based on the intuition that when a manifold in $D$ dimensional space with an intrinsic dimension of $d$ intersects with another manifold, the data variance grows in more than $d$ directions. The proposed method measures local data variances and determines their vector directions. It counts the number of vectors with non-zero variance, which determines the manifold's intrinsic dimension. For detection of the intersection region, the method adapts to the changes in the angular gaps between the corresponding direction vectors of the child and parent using exponential moving averages using a tree structure construction. Accordingly, it includes those data points in the same manifold whose neighborhood is within the adaptive angular difference and eventually identifies the data points in the intersection area of manifolds. Data points whose inclusion in the neighborhood-identified data points increases their intrinsic dimensionality are removed based on data variance and distance. The proposed method performs better than 18 SOTA manifold segmentation methods in ARI and NMI scores over 14 real-world datasets with lesser time complexity and better stability., Comment: 14 pages, 7 figures, 7 tables
Published: 2024

2. Impurities induced vortex lattice melting and turbulence in rotating Bose-Einstein condensates

Author: Boral, Rony, Sarkar, Swarup K., Muruganandam, Paulsamy, and Mishra, Pankaj K.
Subjects: Condensed Matter - Quantum Gases
Abstract: We investigate the impact of various impurities on rotating Bose-Einstein condensates confined within two-dimensional harmonic and optical lattice potentials. Without impurities, the rotating condensates display an organized square lattice pattern of vortices due to the influence of a square optical lattice. The introduction of impurity potentials disrupts this lattice structure, inducing a phase transition from an ordered state to a disordered state. Our analysis encompasses both static and dynamic types of impurities. The static impurities are implemented using a randomly varying potential with a spatially random amplitude. The transformation of the vortex lattice structure, in this case, relies on the strength and lattice constant of the impurity potential. For dynamical impurities, we employ a Gaussian obstacle that orbits around the condensate at a specific distance from its center. In this scenario, the vortex lattice melting occurs beyond a certain threshold radius and frequency of oscillation of the rotating obstacle. We characterize the melting of the vortex lattice due to impurities using various quantities, such as the structure factor and angular momentum. Notably, in the vortex-melted state, the angular momentum follows a power-law dependence with an exponent of approximately $1.73$, regardless of the type of impurity. Finally, we demonstrate the signature of the presence of a turbulent state within the vortex-melted state generated by both static and dynamical impurities., Comment: 19Pages, 23 figures
Published: 2024

3. Implementing a School-Based Health Center Virtual Care Program: A Qualitative Exploration of the School Nurse Perspective

Author: Honora Quinn Burnett, Alyssa Boral, Samantha Schaap, Christy Haas-Howard, and Sonja O'Leary
Abstract: Background: School-based health centers (SBHCs) have the capability to overcome youth barriers to care. Virtual care programs (VCP) facilitate connection between school nurse and off-site SBHC providers and can increase the reach of SBHCs. This project aimed to examine Denver Public School nurses' perspectives of a pilot VCP. Methods: Thirteen semi-structured qualitative interviews were conducted and coded using an inductive approach to identify key themes. Results: Four major themes emerged: (1) obtaining consent, finding space, and capacity are challenges and nurses have suggestions; (2) nurses enjoy feeling like a valued member of a health care team, and providing additional resources to students; (3) nurses perceive benefits in providing free, efficient, higher level of care; (4) adopting novel technology is a facilitator and challenge; limitations included space and privacy. Conclusions: Key findings can be utilized to further inform practice.
Published: 2024
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4. Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Author: Gemini Team, Georgiev, Petko, Lei, Ving Ian, Burnell, Ryan, Bai, Libin, Gulati, Anmol, Tanzer, Garrett, Vincent, Damien, Pan, Zhufeng, Wang, Shibo, Mariooryad, Soroosh, Ding, Yifan, Geng, Xinyang, Alcober, Fred, Frostig, Roy, Omernick, Mark, Walker, Lexi, Paduraru, Cosmin, Sorokin, Christina, Tacchetti, Andrea, Gaffney, Colin, Daruki, Samira, Sercinoglu, Olcan, Gleicher, Zach, Love, Juliette, Voigtlaender, Paul, Jain, Rohan, Surita, Gabriela, Mohamed, Kareem, Blevins, Rory, Ahn, Junwhan, Zhu, Tao, Kawintiranon, Kornraphop, Firat, Orhan, Gu, Yiming, Zhang, Yujing, Rahtz, Matthew, Faruqui, Manaal, Clay, Natalie, Gilmer, Justin, Co-Reyes, JD, Penchev, Ivo, Zhu, Rui, Morioka, Nobuyuki, Hui, Kevin, Haridasan, Krishna, Campos, Victor, Mahdieh, Mahdis, Guo, Mandy, Hassan, Samer, Kilgour, Kevin, Vezer, Arpi, Cheng, Heng-Tze, de Liedekerke, Raoul, Goyal, Siddharth, Barham, Paul, Strouse, DJ, Noury, Seb, Adler, Jonas, Sundararajan, Mukund, Vikram, Sharad, Lepikhin, Dmitry, Paganini, Michela, Garcia, Xavier, Yang, Fan, Valter, Dasha, Trebacz, Maja, Vodrahalli, Kiran, Asawaroengchai, Chulayuth, Ring, Roman, Kalb, Norbert, Soares, Livio Baldini, Brahma, Siddhartha, Steiner, David, Yu, Tianhe, Mentzer, Fabian, He, Antoine, Gonzalez, Lucas, Xu, Bibo, Kaufman, Raphael Lopez, Shafey, Laurent El, Oh, Junhyuk, Hennigan, Tom, Driessche, George van den, Odoom, Seth, Lucic, Mario, Roelofs, Becca, Lall, Sid, Marathe, Amit, Chan, Betty, Ontanon, Santiago, He, Luheng, Teplyashin, Denis, Lai, Jonathan, Crone, Phil, Damoc, Bogdan, Ho, Lewis, Riedel, Sebastian, Lenc, Karel, Yeh, Chih-Kuan, Chowdhery, Aakanksha, Xu, Yang, Kazemi, Mehran, Amid, Ehsan, Petrushkina, Anastasia, Swersky, Kevin, Khodaei, Ali, Chen, Gowoon, Larkin, Chris, Pinto, Mario, Yan, Geng, Badia, Adria Puigdomenech, Patil, Piyush, Hansen, Steven, Orr, Dave, Arnold, Sebastien M. 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Neitz, Alexander, Heitkaemper, Jens, Sinha, Anu, Zhou, Denny, Sun, Yi, Kaed, Charbel, Hulse, Brice, Mishra, Swaroop, Georgaki, Maria, Kudugunta, Sneha, Farabet, Clement, Shafran, Izhak, Vlasic, Daniel, Tsitsulin, Anton, Ananthanarayanan, Rajagopal, Carin, Alen, Su, Guolong, Sun, Pei, V, Shashank, Carvajal, Gabriel, Broder, Josef, Comsa, Iulia, Repina, Alena, Wong, William, Chen, Warren Weilun, Hawkins, Peter, Filonov, Egor, Loher, Lucia, Hirnschall, Christoph, Wang, Weiyi, Ye, Jingchen, Burns, Andrea, Cate, Hardie, Wright, Diana Gage, Piccinini, Federico, Zhang, Lei, Lin, Chu-Cheng, Gog, Ionel, Kulizhskaya, Yana, Sreevatsa, Ashwin, Song, Shuang, Cobo, Luis C., Iyer, Anand, Tekur, Chetan, Garrido, Guillermo, Xiao, Zhuyun, Kemp, Rupert, Zheng, Huaixiu Steven, Li, Hui, Agarwal, Ananth, Ngani, Christel, Goshvadi, Kati, Santamaria-Fernandez, Rebeca, Fica, Wojciech, Chen, Xinyun, Gorgolewski, Chris, Sun, Sean, Garg, Roopal, Ye, Xinyu, Eslami, S. M. Ali, Hua, Nan, Simon, Jon, Joshi, Pratik, Kim, Yelin, Tenney, Ian, Potluri, Sahitya, Thiet, Lam Nguyen, Yuan, Quan, Luisier, Florian, Chronopoulou, Alexandra, Scellato, Salvatore, Srinivasan, Praveen, Chen, Minmin, Koverkathu, Vinod, Dalibard, Valentin, Xu, Yaming, Saeta, Brennan, Anderson, Keith, Sellam, Thibault, Fernando, Nick, Huot, Fantine, Jung, Junehyuk, Varadarajan, Mani, Quinn, Michael, Raul, Amit, Le, Maigo, Habalov, Ruslan, Clark, Jon, Jalan, Komal, Bullard, Kalesha, Singhal, Achintya, Luong, Thang, Wang, Boyu, Rajayogam, Sujeevan, Eisenschlos, Julian, Jia, Johnson, Finchelstein, Daniel, Yakubovich, Alex, Balle, Daniel, Fink, Michael, Agarwal, Sameer, Li, Jing, Dvijotham, Dj, Pal, Shalini, Kang, Kai, Konzelmann, Jaclyn, Beattie, Jennifer, Dousse, Olivier, Wu, Diane, Crocker, Remi, Elkind, Chen, Jonnalagadda, Siddhartha Reddy, Lee, Jong, Holtmann-Rice, Dan, Kallarackal, Krystal, Liu, Rosanne, Vnukov, Denis, Vats, Neera, Invernizzi, Luca, Jafari, Mohsen, Zhou, Huanjie, Taylor, Lilly, Prendki, Jennifer, Wu, Marcus, Eccles, Tom, Liu, Tianqi, Kopparapu, Kavya, Beaufays, Francoise, Angermueller, Christof, Marzoca, Andreea, Sarcar, Shourya, Dib, Hilal, Stanway, Jeff, Perbet, Frank, Trdin, Nejc, Sterneck, Rachel, Khorlin, Andrey, Li, Dinghua, Wu, Xihui, Goenka, Sonam, Madras, David, Goldshtein, Sasha, Gierke, Willi, Zhou, Tong, Liu, Yaxin, Liang, Yannie, White, Anais, Li, Yunjie, Singh, Shreya, Bahargam, Sanaz, Epstein, Mark, Basu, Sujoy, Lao, Li, Ozturel, Adnan, Crous, Carl, Zhai, Alex, Lu, Han, Tung, Zora, Gaur, Neeraj, Walton, Alanna, Dixon, Lucas, Zhang, Ming, Globerson, Amir, Uy, Grant, Bolt, Andrew, Wiles, Olivia, Nasr, Milad, Shumailov, Ilia, Selvi, Marco, Piccinno, Francesco, Aguilar, Ricardo, McCarthy, Sara, Khalman, Misha, Shukla, Mrinal, Galic, Vlado, Carpenter, John, Villela, Kevin, Zhang, Haibin, Richardson, Harry, Martens, James, Bosnjak, Matko, Belle, Shreyas Rammohan, Seibert, Jeff, Alnahlawi, Mahmoud, McWilliams, Brian, Singh, Sankalp, Louis, Annie, Ding, Wen, Popovici, Dan, Simicich, Lenin, Knight, Laura, Mehta, Pulkit, Gupta, Nishesh, Shi, Chongyang, Fatehi, Saaber, Mitrovic, Jovana, Grills, Alex, Pagadora, Joseph, Petrova, Dessie, Eisenbud, Danielle, Zhang, Zhishuai, Yates, Damion, Mittal, Bhavishya, Tripuraneni, Nilesh, Assael, Yannis, Brovelli, Thomas, Jain, Prateek, Velimirovic, Mihajlo, Akbulut, Canfer, Mu, Jiaqi, Macherey, Wolfgang, Kumar, Ravin, Xu, Jun, Qureshi, Haroon, Comanici, Gheorghe, Wiesner, Jeremy, Gong, Zhitao, Ruddock, Anton, Bauer, Matthias, Felt, Nick, GP, Anirudh, Arnab, Anurag, Zelle, Dustin, Rothfuss, Jonas, Rosgen, Bill, Shenoy, Ashish, Seybold, Bryan, Li, Xinjian, Mudigonda, Jayaram, Erdogan, Goker, Xia, Jiawei, Simsa, Jiri, Michi, Andrea, Yao, Yi, Yew, Christopher, Kan, Steven, Caswell, Isaac, Radebaugh, Carey, Elisseeff, Andre, Valenzuela, Pedro, McKinney, Kay, Paterson, Kim, Cui, Albert, Latorre-Chimoto, Eri, Kim, Solomon, Zeng, William, Durden, Ken, Ponnapalli, Priya, Sosea, Tiberiu, Choquette-Choo, Christopher A., Manyika, James, Robenek, Brona, Vashisht, Harsha, Pereira, Sebastien, Lam, Hoi, Velic, Marko, Owusu-Afriyie, Denese, Lee, Katherine, Bolukbasi, Tolga, Parrish, Alicia, Lu, Shawn, Park, Jane, Venkatraman, Balaji, Talbert, Alice, Rosique, Lambert, Cheng, Yuchung, Sozanschi, Andrei, Paszke, Adam, Kumar, Praveen, Austin, Jessica, Li, Lu, Salama, Khalid, Kim, Wooyeol, Dukkipati, Nandita, Baryshnikov, Anthony, Kaplanis, Christos, Sheng, XiangHai, Chervonyi, Yuri, Unlu, Caglar, Casas, Diego de Las, Askham, Harry, Tunyasuvunakool, Kathryn, Gimeno, Felix, Poder, Siim, Kwak, Chester, Miecnikowski, Matt, Dimitriev, Alek, Parisi, Aaron, Liu, Dangyi, Tsai, Tomy, Shevlane, Toby, Kouridi, Christina, Garmon, Drew, Goedeckemeyer, Adrian, Brown, Adam R., Vijayakumar, Anitha, Elqursh, Ali, Jazayeri, Sadegh, Huang, Jin, Carthy, Sara Mc, Hoover, Jay, Kim, Lucy, Kumar, Sandeep, Chen, Wei, Biles, Courtney, Bingham, Garrett, Rosen, Evan, Wang, Lisa, Tan, Qijun, Engel, David, Pongetti, Francesco, de Cesare, Dario, Hwang, Dongseong, Yu, Lily, Pullman, Jennifer, Narayanan, Srini, Levin, Kyle, Gopal, Siddharth, Li, Megan, Aharoni, Asaf, Trinh, Trieu, Lo, Jessica, Casagrande, Norman, Vij, Roopali, Matthey, Loic, Ramadhana, Bramandia, Matthews, Austin, Carey, CJ, Johnson, Matthew, Goranova, Kremena, Shah, Rohin, Ashraf, Shereen, Dasgupta, Kingshuk, Larsen, Rasmus, Wang, Yicheng, Vuyyuru, Manish Reddy, Jiang, Chong, Ijazi, Joana, Osawa, Kazuki, Smith, Celine, Boppana, Ramya Sree, Bilal, Taylan, Koizumi, Yuma, Xu, Ying, Altun, Yasemin, Shabat, Nir, Bariach, Ben, Korchemniy, Alex, Choo, Kiam, Ronneberger, Olaf, Iwuanyanwu, Chimezie, Zhao, Shubin, Soergel, David, Hsieh, Cho-Jui, Cai, Irene, Iqbal, Shariq, Sundermeyer, Martin, Chen, Zhe, Bursztein, Elie, Malaviya, Chaitanya, Biadsy, Fadi, Shroff, Prakash, Dhillon, Inderjit, Latkar, Tejasi, Dyer, Chris, Forbes, Hannah, Nicosia, Massimo, Nikolaev, Vitaly, Greene, Somer, Georgiev, Marin, Wang, Pidong, Martin, Nina, Sedghi, Hanie, Zhang, John, Banzal, Praseem, Fritz, Doug, Rao, Vikram, Wang, Xuezhi, Zhang, Jiageng, Patraucean, Viorica, Du, Dayou, Mordatch, Igor, Jurin, Ivan, Liu, Lewis, Dubey, Ayush, Mohan, Abhi, Nowakowski, Janek, Ion, Vlad-Doru, Wei, Nan, Tojo, Reiko, Raad, Maria Abi, Hudson, Drew A., Keshava, Vaishakh, Agrawal, Shubham, Ramirez, Kevin, Wu, Zhichun, Nguyen, Hoang, Liu, Ji, Sewak, Madhavi, Petrini, Bryce, Choi, DongHyun, Philips, Ivan, Wang, Ziyue, Bica, Ioana, Garg, Ankush, Wilkiewicz, Jarek, Agrawal, Priyanka, Guo, Danhao, Xue, Emily, Shaik, Naseer, Leach, Andrew, Khan, Sadh MNM, Wiesinger, Julia, Jerome, Sammy, Chakladar, Abhishek, Wang, Alek Wenjiao, Ornduff, Tina, Abu, Folake, Ghaffarkhah, Alireza, Wainwright, Marcus, Cortes, Mario, Liu, Frederick, Maynez, Joshua, Terzis, Andreas, Samangouei, Pouya, Mansour, Riham, Kępa, Tomasz, Aubet, François-Xavier, Algymr, Anton, Banica, Dan, Weisz, Agoston, Orban, Andras, Senges, Alexandre, Andrejczuk, Ewa, Geller, Mark, Santo, Niccolo Dal, Anklin, Valentin, Merey, Majd Al, Baeuml, Martin, Strohman, Trevor, Bai, Junwen, Petrov, Slav, Wu, Yonghui, Hassabis, Demis, Kavukcuoglu, Koray, Dean, Jeffrey, and Vinyals, Oriol
Subjects: Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract: In this report, we introduce the Gemini 1.5 family of models, representing the next generation of highly compute-efficient multimodal models 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. The family includes two new models: (1) an updated Gemini 1.5 Pro, which exceeds the February version on the great majority of capabilities and benchmarks; (2) Gemini 1.5 Flash, a more lightweight variant designed for efficiency with minimal regression in quality. Gemini 1.5 models achieve near-perfect recall on long-context retrieval tasks across modalities, improve the state-of-the-art in long-document QA, long-video QA and long-context ASR, and match or surpass Gemini 1.0 Ultra's state-of-the-art performance across a broad set of benchmarks. Studying the limits of Gemini 1.5'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 3.0 (200k) and GPT-4 Turbo (128k). Finally, we highlight real-world use cases, such as Gemini 1.5 collaborating with professionals on completing their tasks achieving 26 to 75% time savings across 10 different job categories, as well as 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

5. Prediction models using maximum entropy for suitable habitats in the present and future scenarios for rare and endemic Codonopsis affinis in Darjeeling eastern Himalaya

Author: Boral, Debasruti and Moktan, Saurav
Published: 2024
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6. 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, 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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, Andreev, Alek, He, Antoine, Hui, Kevin, Kashem, Sheleem, Subramanya, Amar, Hsiao, Sissie, Hassabis, Demis, Kavukcuoglu, Koray, Sadovsky, Adam, Le, Quoc, Strohman, Trevor, Wu, Yonghui, Petrov, Slav, Dean, Jeffrey, and Vinyals, Oriol
Subjects: Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition
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

7. ISAApp – Image Based Smart Attendance Application

Author: Dutta, Aritra, Suseela, G., Niranjana, G., Boral, Pushpita, Gupta, Pranav, Pal, Subha Bal, Ghosh, Ashish, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Geetha, R., editor, Dao, Nhu-Ngoc, editor, and Khalid, Saeed, editor
Published: 2025
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8. An Analysis of the Contaminants on Otoscopes of Otolaryngology Residents: An Observational Study

Author: Havaldar, Rajesh Radhakrishna, Vagarali, Manjula A, Belaldavar, Basavaraj P, Redkar, Aditya Achyut, and Boral, Prakriti
Published: 2024
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9. Transitioning from Aflibercept to Biosimilar Ranibizumab in Diabetic Macular Edema (DME): (The TRANSFORM-DME Trial) a Multicenter Observational Study

Author: Chakraborty D, Sinha TK, Maiti A, Boral SK, Das A, Mondal S, Nandi K, and Bhattacharya R
Subjects: diabetic macular edema, anti vegf, aflibercept, biosimilar ranibizumab, Ophthalmology, RE1-994
Abstract: Debdulal Chakraborty,1 Tushar Kanti Sinha,1 Aniruddha Maiti,2 Subhendu Kumar Boral,1 Arnab Das,1 Soumen Mondal,1 Krishnendu Nandi,3 Ranabir Bhattacharya1 1Department of Vitreoretinal Services, Disha Eye Hospitals, Kolkata, West Bengal, India; 2Department of Vitreoretinal Services, Global Eye Hospitals, Kolkata, West Bengal, India; 3Department of Vitreoretinal Services, Netralayam Superspeciality Eye Care, Kolkata, West Bengal, IndiaCorrespondence: Debdulal Chakraborty, Department of Vitreo-Retinal Services, Disha Eye Hospitals, Kolkata, West Bengal, India, Tel +91 33 6636 0000, Email devdc@rediffmail.comPurpose: To evaluate visual and anatomical outcomes following a switch from intravitreal Aflibercept (IVI AFL) (T1) to biosimilar Ranibizumab (B-RBZ) (T2) in patients with diabetic macular edema (DME).Methods: This was a multicenter observational study, analysing medical records of consecutive, treatment-naïve centre-involving DME patients having a baseline visual acuity (VA) of ≥ 55 Early Treatment Diabetic Retinopathy Study (ETDRS) letters. DME patients, having received monthly loading doses of IVI AFL(T1) and responsive to it, who subsequently shifted to B-RBZ(T2) motivated by financial constraints rather than a lack of efficacy to IVI AFL were identified.Results: This study included 57 participants (mean age: 54.23 ± 6.91 years), with 80.7% male patients. VA improved during T1, from 61.4 ± 11.74 ETDRS letters at baseline to 72.7 ± 8.05 ETDRS letters (mean change: +11.2 letters, 95% CI: 9.1 to 13.4; p < 0.001). During T2, VA declined slightly over 12 months with a mean VA of 69.9 ± 3.78 ETDRS letters at the 12-month mark (+8.5 letters from baseline; p < 0.001). Mean central macular thickness (CMT) during T1 reduced from 411.9 ± 34.62 μm at baseline to 279.3 ± 9.96 μm (mean change: − 132.6 μm, 95% CI: − 142.2 to − 122.9 μm; p < 0.001). CMT remained stable over the 12-month follow-up period, with minimal fluctuations. Subretinal fluid (SRF) and intra retinal fluid (IRF) were present in 84.2% and 91.2% of eyes, respectively, decreasing to 5.3% and 7.0% at the time of switch (p < 0.001). In T2 phase, 22.8% and 21.1% exhibited SRF and IRF, respectively, at the end of the study.Conclusion: Transitioning to biosimilar Ranibizumab (Razumab) after initial treatment with aflibercept in patients with DME preserved visual and anatomical benefits over a 12-month period, with only minor variations in SRF and IRF. These results underscore the efficacy of biosimilar Ranibizumab as a cost-effective option for managing DME.Keywords: diabetic macular edema, anti VEGF, aflibercept, biosimilar ranibizumab
Published: 2024

10. User-defined Event Sampling and Uncertainty Quantification in Diffusion Models for Physical Dynamical Systems

Author: Finzi, Marc, Boral, Anudhyan, Wilson, Andrew Gordon, Sha, Fei, and Zepeda-Núñez, Leonardo
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract: Diffusion models are a class of probabilistic generative models that have been widely used as a prior for image processing tasks like text conditional generation and inpainting. We demonstrate that these models can be adapted to make predictions and provide uncertainty quantification for chaotic dynamical systems. In these applications, diffusion models can implicitly represent knowledge about outliers and extreme events; however, querying that knowledge through conditional sampling or measuring probabilities is surprisingly difficult. Existing methods for conditional sampling at inference time seek mainly to enforce the constraints, which is insufficient to match the statistics of the distribution or compute the probability of the chosen events. To achieve these ends, optimally one would use the conditional score function, but its computation is typically intractable. In this work, we develop a probabilistic approximation scheme for the conditional score function which provably converges to the true distribution as the noise level decreases. With this scheme we are able to sample conditionally on nonlinear userdefined events at inference time, and matches data statistics even when sampling from the tails of the distribution., Comment: ICML 2023 Conference
Published: 2023

11. Neural Ideal Large Eddy Simulation: Modeling Turbulence with Neural Stochastic Differential Equations

Author: Boral, Anudhyan, Wan, Zhong Yi, Zepeda-Núñez, Leonardo, Lottes, James, Wang, Qing, Chen, Yi-fan, Anderson, John Roberts, and Sha, Fei
Subjects: Computer Science - Machine Learning, Mathematics - Numerical Analysis
Abstract: We introduce a data-driven learning framework that assimilates two powerful ideas: ideal large eddy simulation (LES) from turbulence closure modeling and neural stochastic differential equations (SDE) for stochastic modeling. The ideal LES models the LES flow by treating each full-order trajectory as a random realization of the underlying dynamics, as such, the effect of small-scales is marginalized to obtain the deterministic evolution of the LES state. However, ideal LES is analytically intractable. In our work, we use a latent neural SDE to model the evolution of the stochastic process and an encoder-decoder pair for transforming between the latent space and the desired ideal flow field. This stands in sharp contrast to other types of neural parameterization of closure models where each trajectory is treated as a deterministic realization of the dynamics. We show the effectiveness of our approach (niLES - neural ideal LES) on a challenging chaotic dynamical system: Kolmogorov flow at a Reynolds number of 20,000. Compared to competing methods, our method can handle non-uniform geometries using unstructured meshes seamlessly. In particular, niLES leads to trajectories with more accurate statistics and enhances stability, particularly for long-horizon rollouts., Comment: 18 pages
Published: 2023

12. Modelling current and future potential distribution of medicinal orchids in Darjeeling eastern Himalaya

Author: Boral, Debasruti and Moktan, Saurav
Published: 2024
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13. Debias Coarsely, Sample Conditionally: Statistical Downscaling through Optimal Transport and Probabilistic Diffusion Models

Author: Wan, Zhong Yi, Baptista, Ricardo, Chen, Yi-fan, Anderson, John, Boral, Anudhyan, Sha, Fei, and Zepeda-Núñez, Leonardo
Subjects: Computer Science - Machine Learning, Physics - Applied Physics
Abstract: We introduce a two-stage probabilistic framework for statistical downscaling using unpaired data. Statistical downscaling seeks a probabilistic map to transform low-resolution data from a biased coarse-grained numerical scheme to high-resolution data that is consistent with a high-fidelity scheme. Our framework tackles the problem by composing two transformations: (i) a debiasing step via an optimal transport map, and (ii) an upsampling step achieved by a probabilistic diffusion model with a posteriori conditional sampling. This approach characterizes a conditional distribution without needing paired data, and faithfully recovers relevant physical statistics from biased samples. We demonstrate the utility of the proposed approach on one- and two-dimensional fluid flow problems, which are representative of the core difficulties present in numerical simulations of weather and climate. Our method produces realistic high-resolution outputs from low-resolution inputs, by upsampling resolutions of 8x and 16x. Moreover, our procedure correctly matches the statistics of physical quantities, even when the low-frequency content of the inputs and outputs do not match, a crucial but difficult-to-satisfy assumption needed by current state-of-the-art alternatives. Code for this work is available at: https://github.com/google-research/swirl-dynamics/tree/main/swirl_dynamics/projects/probabilistic_diffusion., Comment: NeurIPS 2023 (spotlight)
Published: 2023

14. Transitioning from Aflibercept to Biosimilar Ranibizumab in Neovascular AMD (The TRANSFORM Trial): A Multicenter Observational Study

Author: Chakraborty D, Boral S, Sinha TK, Das A, Mukherjee A, Majumdar S, Bhattacharya R, and Maitra R
Subjects: neovascular amd, aflibercept, biosimilar ranibizumab, subretinal fluid, intraretinal fluid, Ophthalmology, RE1-994
Abstract: Debdulal Chakraborty,1 Subhendu Boral,1 Tushar Kanti Sinha,1 Arnab Das,1 Angshuman Mukherjee,1 Saptorshi Majumdar,1 Ranabir Bhattacharya,2 Ritobroto Maitra3 1Department of Vitreoretinal Services, Disha Eye Hospitals, Kolkata, West Bengal, India; 2Department of MIS, Disha Eye Hospitals, Kolkata, West Bengal, India; 3Radical Health Tech, New Delhi, IndiaCorrespondence: Debdulal Chakraborty, Department of Vitreoretinal services; Disha Eye Hospitals, Kolkata, West Bengal, India, Tel +91 33 66360000, Email devdc@rediffmail.comPurpose: This study investigates the efficacy of transitioning patients with neovascular age-related macular degeneration (nAMD) from aflibercept (T1) to biosimilar ranibizumab (T2), an approach not previously documented in literature.Methods: In this multicenter observational study, patients over 50 years of age with nAMD were shifted from intravitreal aflibercept (IVI AFL) to biosimilar ranibizumab (B-RBZ) due to financial constraints. This study employed standardized ophthalmological methods to assess visual acuity (VA), central macular thickness (CMT), and subretinal and intraretinal fluid. Statistical analyses included paired t-tests, Wilcoxon signed-rank tests, and linear regression.Results: A total of 29 eyes (12 males and 17 females) were analyzed. Mean age was 72.55 ± 6.43 years. VA improved significantly during T1, with a mean increase from 55.0 ± 10.2 to 70.0 ± 8.5 ETDRS letters at the switch time point (p < 0.01), then a slight decrease to 62.3 ± 8.9 at 12 months (p < 0.05) was noted during T2. The mean CMT decreased notably from 400 ± 50 to 290 ± 45 μm at the switch. The final CMT at 12 months after switching to B-RBZ was 280 ± 40 μm (p < 0.01). There was a significant decrease in the retinal and intra retinal fluid during T1, followed by a gradual increase during T2. A significant correlation (p < 0.05) was noted between the presence of intraretinal fluid and increased injection frequency of B-RBZ.Conclusion: The switch from IVI AFL to IVI B-RBZ in patients with nAMD demonstrated efficacy in maintaining the VA and macular anatomy, with some challenges in fluid management.Keywords: neovascular AMD, aflibercept, biosimilar ranibizumab, subretinal fluid, intraretinal fluid
Published: 2024

15. Evolve Smoothly, Fit Consistently: Learning Smooth Latent Dynamics For Advection-Dominated Systems

Author: Wan, Zhong Yi, Zepeda-Núñez, Leonardo, Boral, Anudhyan, and Sha, Fei
Subjects: Computer Science - Machine Learning, Physics - Computational Physics
Abstract: We present a data-driven, space-time continuous framework to learn surrogate models for complex physical systems described by advection-dominated partial differential equations. Those systems have slow-decaying Kolmogorov n-width that hinders standard methods, including reduced order modeling, from producing high-fidelity simulations at low cost. In this work, we construct hypernetwork-based latent dynamical models directly on the parameter space of a compact representation network. We leverage the expressive power of the network and a specially designed consistency-inducing regularization to obtain latent trajectories that are both low-dimensional and smooth. These properties render our surrogate models highly efficient at inference time. We show the efficacy of our framework by learning models that generate accurate multi-step rollout predictions at much faster inference speed compared to competitors, for several challenging examples., Comment: 25 pages, 9 figures
Published: 2023

16. Impact of Compressed Natural Gas in Changing the Air Quality of Agartala City with reference to CO2 Emissions

Author: Bulti Das, Ashish K. Reji, Tuhin Kanti Ray, and Eshita Boral
Subjects: Chemical engineering, TP155-156, Computer engineering. Computer hardware, TK7885-7895
Abstract: Transport sector is one of the very significant sources of air pollution. The environmental effects of transport are huge because transport sectors are the major users of energy, and it burns most of the world's petroleum. Within the transport sector, road transport is the largest contributor to air pollution. Carbon emissions from conventional fuels such as petrol and diesel contribute significantly to this pollution. Sustainable approach to urban transport addresses the environmental concerns with the need to provide affordable mobility choices to the rapidly growing population of urban areas. The aim is to validate Compressed Natural Gas (CNG) as a safe alternative vehicular fuel to reduce CO2 emission in Agartala city. For that reason, an attempt to conversion of vehicles running on harmful conventional fuels into CNG fuel in the Agartala Municipal Corporation (AMC) area under three intervention scenarios has been undertaken and analyzed. The result reveals a huge change in environmental status, which makes it appropriate to conclude that the use of CNG as a vehicular fuel is the best sustainable approach in urban surface transport to significantly reduce CO2 emission.
Published: 2024

17. Integrated Fuzzy MCDM Frameworks in Risk Prioritization of Failure Modes

Author: Boral, Soumava, Chaturvedi, Sanjay K., Liu, Yiliu, Howard, Ian, Varde, Prabhakar V., Series Editor, Verma, Ajit Kumar, Series Editor, Kumar, Uday, Series Editor, and Karanki, Durga Rao, editor
Published: 2024
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18. Efficacy of antibiotic combinations in an experimental sepsis model with Pseudomonas aeruginosa

Author: Aktas, Zerrin, Sonmez, Nese, Oksuz, Lutfiye, Boral, Ozden, Issever, Halim, and Oncul, Oral
Published: 2023
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19. Aflibercept vs. dexamethasone implant for recalcitrant diabetic macular edema in pseudophakic eyes – 1-year outcomes from a quazi-randomized study in India

Author: Debdulal Chakraborty, Soumen Mondal, Sabyasachi Sengupta, Aniruddha Maiti, Subhendu Boral, Arnab Das, Tushar K Sinha, and Krishnendu Nandi
Subjects: aflibercept, anti vegf, dexamethasone, ranibizumab, recalcitrant diabetic macular edema, Ophthalmology, RE1-994
Abstract: Purpose: To assess the safety and efficacy of intravitreal Aflibercept (IVA) versus dexamethasone (DEX) implant for treating recalcitrant diabetic macular edema (DME) in pseudophakic eyes at 1-year follow-up. Design: Retrospective comparative case series. Participants: Data of all patients diagnosed with DME between January 2019 and December 2021, who underwent 4-monthly doses of intravitreal ranibizumab but had persistent DME [central macular thickness (CMT) within 10% of baseline value] were extracted from a computerized database. Of these, only pseudophakic eyes that underwent either IVA or DEX implant and had at least 1-year follow-up were included for analysis. Methods: DEX implant was preferred before December 2020 and IVA after this time point. In the IVA group, patients were followed up every month while DEX were followed at least every 3 months. Reinjections were considered when vision dropped by at least 1 Snellen’s line or CMT increased by at least 10% from the previous visit in both groups. Main Outcome Measures: Comparison of change in vision and CMT at 1-year follow-up in DEX versus IVA groups. Results: Eighty-four eyes of 84 patients aged 54.4 + 4.4 years were included, 39 (46%) received DEX and 45 (54%) received IVA. Groups were comparable for baseline vision and CMT. Vision improved equally in both groups from 0.83 + 0.15 logMAR to 0.52 + 0.10 logMAR at 3 months (P < 0.01) and then stabilized till 1 year. However, eyes in the IVA group were 6.5 times more likely (Odds ratio = 6.45, 95% CI = 1.3 – 31.9) to achieve >3-line improvement in vision. The CMT reduction was also comparable between groups (-169 + 51 in DEX vs. -174 + 49 in IVA, P = 0.67). More eyes in the IVA group required >3 injections (91% vs. 69% in DEX, P = 0.01). The IOP was significantly higher at 6 and 9 months in the DEX group and 5 eyes (13%) required IOP lowering medications. Conclusion: In pseudophakic eyes with recalcitrant DME not responding to ranibizumab, switching to IVA or DEX implant results in equal visual improvement and CMT reduction. Though >3-line improvement occurs more frequently with IVA, this comes at the expense of a greater number of injections and follow-up visits.
Published: 2024
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20. Brolucizumab versus aflibercept for recalcitrant diabetic macular edema in Indian real-world scenario – The BRADIR study

Author: Debdulal Chakraborty, Ashish Sharma, Soumen Mondal, Jay Sheth, Tushar Kanti Sinha, Subhendu Boral, Angshuman Mukherjee, Ranabir Bhattacharya, and Ritobroto Maitra
Subjects: Brolucizumab, Aflibercept, Diabetic macular edema, Vascular endothelial growth factor, Diabetic retinopathy, Ophthalmology, RE1-994
Abstract: Purpose: To compare the safety and efficacy of aflibercept with brolucizumab for recalcitrant diabetic macular edema (DME). Observations: At week 52, no significant visual improvement was noted in the eyes treated with either brolucizumab (P = 0.527) or aflibercept (P = 0.393). The CMT decreased significantly after brolucizumab therapy (P = 0.012), but not with aflibercept (P = 0.284) at 52 weeks. The proportion of patients with IRF and SRF reduced significantly in both arms. The mean number of brolucizumab injections was significantly lower (3.93[±1.28]) than aflibercept (4.75[±1.62]) (P = 0.037) over the 52 weeks. At 52 weeks, 76.67 % of eyes treated with brolucizumab attained full macular dryness (CMT
Published: 2024
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21. Accelerating Physics Simulations with TPUs: An Inundation Modeling Example

Author: Pierce, Damien, Hu, R. Lily, Shafi, Yusef, Boral, Anudhyan, Anisimov, Vladimir, Nevo, Sella, and Chen, Yi-fan
Subjects: Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Computational Engineering, Finance, and Science, Physics - Computational Physics
Abstract: Recent advancements in hardware accelerators such as Tensor Processing Units (TPUs) speed up computation time relative to Central Processing Units (CPUs) not only for machine learning but, as demonstrated here, also for scientific modeling and computer simulations. To study TPU hardware for distributed scientific computing, we solve partial differential equations (PDEs) for the physics simulation of fluids to model riverine floods. We demonstrate that TPUs achieve a two orders of magnitude speedup over CPUs. Running physics simulations on TPUs is publicly accessible via the Google Cloud Platform, and we release a Python interactive notebook version of the simulation., Comment: 14 pages, 10 figures. Accepted for publication in The International Journal of High Performance Computing Applications
Published: 2022

22. A study combining experimental, computationaland machine learning approaches on the removal of tartrazine dye using carbon nanotubes

Author: Dhar, Abhishek, Behera, Anil Kumar, Gupta, Kaushik, Chatterjee, Dipta, Boral, Nilavo, Vekariya, Rohit L., Sarkar, Priyatosh, and Sen, Anik
Published: 2024
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23. Use of term reference infants in assessing the developmental outcome of extremely preterm infants: lessons learned in a multicenter study

Author: Green, Charles E., Tyson, Jon E., Heyne, Roy J., Hintz, Susan R., Vohr, Betty R., Bann, Carla M., Das, Abhik, Bell, Edward F., Debsareea, Sana Boral, Stephens, Emily, Gantz, Marie G., Petrie Huitema, Carolyn M., Johnson, Karen J., Watterberg, Kristi L., Mosquera, Ricardo, Peralta-Carcelen, Myriam, Wilson-Costello, Deanne E., Colaizy, Tarah T., Maitre, Nathalie L., Merhar, Stephanie L., Adams-Chapman, Ira, Fuller, Janell, Hartley-McAndrew, Michelle E., Malcolm, William F., Winter, Sarah, Duncan, Andrea F., Myer, Gary J., Kicklighter, Stephen D., Wyckoff, Myra H., DeMauro, Sara B., Hibbs, Anna Maria, Stoll, Barbara J., Carlo, Waldemar A., Van Meurs, Krisa P., Rysavy, Matthew A., Patel, Ravi M., Sánchez, Pablo J., Laptook, Abbot R., Cotten, C. Michael, D’Angio, Carl T., and Walsh, Michele C.
Published: 2023
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24. CARD: Comprehensive approach based on relative difference for decision-making problems with dual evaluation forms − Application to sustainable renewable energy selection

Author: Seiti, Hamidreza, Boral, Soumava, Hafezalkotob, Arian, Ben-Amor, Sarah, Hafezalkotob, Ashkan, and Makui, Ahmad
Published: 2024
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25. Recent developments on carbon neutrality through carbon dioxide capture and utilization with clean hydrogen for production of alternative fuels for smart cities

Author: Goren, A. Yagmur, Dincer, Ibrahim, Gogoi, Subrata Borgohain, Boral, Pranab, and Patel, Dipal
Published: 2024
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26. The intrinsically disordered transactivation region of HOXA9 regulates its function by auto-inhibition of its DNA-binding activity

Author: Saibo, Nikita V., Maiti, Snigdha, Boral, Soumendu, Banerjee, Puja, Kushwaha, Tushar, Inampudi, Krishna K., Goswami, Ritobrata, and De, Soumya
Published: 2024
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27. Psychometric evaluation of the Indolent Systemic Mastocytosis Symptom Assessment Form (ISM-SAF©) and determination of a threshold score for moderate symptoms

Author: Shields, Alan L., Taylor, Fiona, Lamoureux, Roger E., Padilla, Brad, Severson, Kas, Green, Tanya, Boral, Anthony L., Akin, Cem, Siebenhaar, Frank, and Mar, Brenton
Published: 2023
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28. Does Emerging Carbapenem Resistance in Acinetobacter baumannii Increase the Case Fatality Rate? Systematic Review and Meta-Analysis

Author: Jale Boral, Fatihan Pınarlık, Güz Ekinci, Füsun Can, and Önder Ergönül
Subjects: Acinetobacter baumannii, systematic review, carbapenem resistance, mortality rate, molecular epidemiology, Other systems of medicine, RZ201-999
Abstract: Background: In the era of rising carbapenem resistance, we aimed to investigate the change in mortality rate and positivity of carbapenemase genes in Acinetobacter baumannii. Methods: Preferred Reporting Items for Systematic Review (PRISMA) guidelines were adopted in this systematic review. Our literature search included the Cochrane Library, Pubmed, Scopus, Web of Science, Medline, Tubitak TR Dizin, and Harman databases for studies dating back from 2003 to 2023 reporting bloodstream A. baumannii infections in Türkiye. A simple linear regression model was used to determine the association between resistance, mortality, and time. Results: A total of 1717 studies were identified through a literature search, and 21 articles were selected based on the availability of the data regarding mortality and resistance rate (four articles) or the molecular epidemiology of carbapenem-resistant A. baumannii (17 articles) in Türkiye. From 2007 to 2018, the carbapenem resistance rate increased (p = 0.025). The OXA-23 and OXA-58 positivities were inversely correlated (p = 0.025). Conclusions: Despite the emergence of carbapenem resistance, mortality did not increase in parallel, which may be due to improved medical advancements or the fitness cost of bacteria upon prolonged antimicrobial exposure. Therefore, we suggest further global research with the foresight to assess clonal relatedness that might affect the carbapenem resistance rate.
Published: 2023
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29. Complete manuscript title: role of sub-silicone oil application of triamcinolone acetonide (TA) drops on outcomes after 360° relaxing retinectomy: a pilot study

Author: Boral, Subhendu Kumar, Agarwal, Deepak, Das, Arnab, and Chakraborty, Debdulal
Published: 2023
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30. Archival influenza virus genomes from Europe reveal genomic variability during the 1918 pandemic

Author: Patrono, Livia V, Vrancken, Bram, Budt, Matthias, Düx, Ariane, Lequime, Sebastian, Boral, Sengül, Gilbert, M Thomas P, Gogarten, Jan F, Hoffmann, Luisa, Horst, David, Merkel, Kevin, Morens, David, Prepoint, Baptiste, Schlotterbeck, Jasmin, Schuenemann, Verena J, Suchard, Marc A, Taubenberger, Jeffery K, Tenkhoff, Luisa, Urban, Christian, Widulin, Navena, Winter, Eduard, Worobey, Michael, Schnalke, Thomas, Wolff, Thorsten, Lemey, Philippe, and Calvignac-Spencer, Sébastien
Subjects: Influenza, Infectious Diseases, Pneumonia & Influenza, Biodefense, Vaccine Related, Human Genome, Prevention, Emerging Infectious Diseases, Genetics, 2.2 Factors relating to the physical environment, Aetiology, Infection, Genome, Viral, Genomics, Humans, Influenza A Virus, H1N1 Subtype, Influenza A virus, Influenza, Human
Abstract: The 1918 influenza pandemic was the deadliest respiratory pandemic of the 20th century and determined the genomic make-up of subsequent human influenza A viruses (IAV). Here, we analyze both the first 1918 IAV genomes from Europe and the first from samples prior to the autumn peak. 1918 IAV genomic diversity is consistent with a combination of local transmission and long-distance dispersal events. Comparison of genomes before and during the pandemic peak shows variation at two sites in the nucleoprotein gene associated with resistance to host antiviral response, pointing at a possible adaptation of 1918 IAV to humans. Finally, local molecular clock modeling suggests a pure pandemic descent of seasonal H1N1 IAV as an alternative to the hypothesis of origination through an intrasubtype reassortment.
Published: 2022

31. User-defined Event Sampling and Uncertainty Quantification in Diffusion Models for Physical Dynamical Systems.

Author: Marc Anton Finzi, Anudhyan Boral, Andrew Gordon Wilson, Fei Sha, and Leonardo Zepeda-Núñez
Published: 2023

32. Transcriptomic Analysis of CTCs

Author: Vishnoi, Monika, Boral, Debasish, Marchetti, Dario, El-Deiry, Wafik, Series Editor, Cote, Richard J., editor, and Lianidou, Evi, editor
Published: 2023
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33. An Exercise on Valuation of Urban Heritage Site, A Comparative Study of Victoria Memorial Hall and Indian Museum, Kolkata

Author: Ray, Tuhin Kanti, Sarkar, Pallavi, Das, Bulti, Boral, Eshita, Sahu, Abhay Sankar, editor, and Das Chatterjee, Nilanjana, editor
Published: 2023
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34. Nuclear Magnetic Resonance Spectroscopy to Analyse Protein Folding and Dynamics

Author: Saibo, Nikita V., Boral, Soumendu, Saha, Rituparna, Das, Amit K., De, Soumya, Saudagar, Prakash, editor, and Tripathi, Timir, editor
Published: 2023
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35. An Assessment of Traffic Noise Level in Agartala Municipal Corporation Using Geo-spatial Technology in Tripura, India

Author: Debnath, Prajnamita, Ghosh, Sajal, Kundu, Debasish, Debnath, Jatan, Ray, Tuhin Kanti, Boral, Eshita, Pradhan, Biswajeet, Series Editor, Shit, Pravat Kumar, Series Editor, Bhunia, Gouri Sankar, Series Editor, Adhikary, Partha Pratim, Series Editor, Pourghasemi, Hamid Reza, Series Editor, Rahman, Atiqur, editor, Sen Roy, Shouraseni, editor, Talukdar, Swapan, editor, and Shahfahad, editor
Published: 2023
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36. Design Optimization for Heat Transfer Through a Circular Pipe

Author: Dutta, Souvik, Boral, Ayush, Das, Anwesha, Chaubdar, Pooja, Harichandan, A. B., Cavas-Martínez, Francisco, Editorial Board Member, Chaari, Fakher, Series Editor, di Mare, Francesca, Editorial Board Member, Gherardini, Francesco, Series Editor, Haddar, Mohamed, Editorial Board Member, Ivanov, Vitalii, Series Editor, Kwon, Young W., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Revankar, Shripad, editor, Muduli, Kamalakanta, editor, and Sahu, Debjyoti, editor
Published: 2023
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37. Development of Rayleigh Taylor Instability at Various Atwood Numbers—A Review

Author: Boral, Ayush, Dutta, Souvik, Kumar, Ankit, Chaubdar, Pooja, Harichandan, A. B., Cavas-Martínez, Francisco, Editorial Board Member, Chaari, Fakher, Series Editor, di Mare, Francesca, Editorial Board Member, Gherardini, Francesco, Series Editor, Haddar, Mohamed, Editorial Board Member, Ivanov, Vitalii, Series Editor, Kwon, Young W., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Revankar, Shripad, editor, Muduli, Kamalakanta, editor, and Sahu, Debjyoti, editor
Published: 2023
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38. Stability and dynamics of extradenticle modulates its function

Author: Singh, Aakanksha, Acharya, Bidisha, Mukherjee, Beas, Boorla, Veda Sheersh, Boral, Soumendu, Maiti, Snigdha, and De, Soumya
Published: 2024
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39. Flexural-gravity wave scattering due to a crack in a floating ice sheet in the perspective of wave blocking in a three-layer fluid

Author: Barman, S.C., Boral, S., and Sahoo, T.
Published: 2024
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40. Stability and dynamics of extradenticle modulates its function

Author: Aakanksha Singh, Bidisha Acharya, Beas Mukherjee, Veda Sheersh Boorla, Soumendu Boral, Snigdha Maiti, and Soumya De
Subjects: Transcription factor, Protein-DNA interaction, NMR spectroscopy, MD simulation, Hydrogen exchange, Biology (General), QH301-705.5
Abstract: Extradenticle (EXD) is a partner protein of the HOX transcription factors and plays an important role in the development of Drosophila. It confers increased affinity and specificity of DNA-binding to the HOX proteins. However, the DNA-binding homeodomain of EXD has a significantly weaker affinity to DNA compared to the HOX homeodomains. Here, we show that a glycine residue (G290) in the middle of the EXD DNA-binding helix primarily results in this weaker binding. Glycine destabilizes helices. To probe its role in the stability and function of the protein, G290 was mutated to alanine. The intrinsic stability of the DNA-binding helix increased in the G290A mutant as observed by NMR studies and molecular dynamics (MD) simulation. Also, NMR dynamics and MD simulation show that dynamic motions present in the wild-type protein are quenched in the mutant. This in turn resulted in increased stability of the entire homeodomain (ΔΔGG→A of −2.6 kcal/mol). Increased protein stability resulted in three-fold better DNA-binding affinity of the mutant as compared to the wild-type protein. Molecular mechanics with generalized Born and surface area solvation (MMGBSA) analysis of our MD simulation on DNA-bound models of both wild-type and mutant proteins shows that the contribution to binding is enhanced for most of the interface residues in the mutant compared to the wild-type. Interestingly, the flexible N-terminal arm makes more stable contact with the DNA minor groove in the mutant. We found that the two interaction sites i.e. the DNA-binding helix and the unstructured N-terminal arm influence each other via the bound DNA. These results provide an interesting conundrum: alanine at position 290 enhances both the stability and the DNA-binding affinity of the protein, however, evolution prefers glycine at this position. We have provided several plausible explanations for this apparent conundrum. The function of the EXD as a HOX co-factor requires its ability to discriminate similar DNA sequences, which is most likely compromised by the quenching of its flexibility and enhancement of its stability and DNA-binding affinity.
Published: 2024
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41. Biosimilar versus InnovAtor MoLecule of RAnibizumab in Neovascular Age-Related MaCular DEgeneration (The BALANCE Trial): Real-World Evidence

Author: Chakraborty D, Mondal S, Boral S, Das A, Sinha TK, Majumdar S, Bhattacharya R, and Maitra R
Subjects: neovascular age-related macular degeneration, anti-vegf, ranibizumab, biosimilar ranibizumab, Ophthalmology, RE1-994
Abstract: Debdulal Chakraborty,1 Soumen Mondal,1 Subhendu Boral,1 Arnab Das,1 Tushar Kanti Sinha,1 Saptorshi Majumdar,1 Ranabir Bhattacharya,2 Ritobroto Maitra3 1Department of Vitreoretinal Services, Disha Eye Hospitals, Kolkata, West Bengal, India; 2Department of MIS, Disha Eye Hospitals, Kolkata, West Bengal, India; 3Radical Health Tech, New Delhi, IndiaCorrespondence: Debdulal Chakraborty, Department of Vitreoretinal services, Disha Eye Hospitals, Kolkata, West Bengal, India, Tel +91 33 66360000, Email devdc@rediffmail.comPurpose: To analyse outcomes of innovator ranibizumab (IRM) (Lucentis) and biosimilar ranibizumab (BRM) (Razumab) in Indian eyes with neovascular age-related macular degeneration (nAMD).Methods: Retrospective observational study in nAMD patients, who were treated with IRM or BRM (3 loading doses followed by pro re nata (PRN). Primary outcome measures were change in best corrected visual acuity (BCVA) and central macular thickness (CMT) along with safety analysis. Secondary outcomes measures were changes in the subretinal fluid (SRF) and intraretinal fluid (IRF).Results: Inclusion criteria were satisfied in 164 eyes (60.74%). A total of 87 eyes were treated with IRM, and 77 eyes received BRM. Baseline BCVA was 0.57± 0.27 logMAR in IRM group and 0.61± 0.25 in the BRM group. At 3, 6, 9, and 12 months BCVA was 0.27± 0.22 (p< 0.0001), 0.34± 0.23 (p< 0.0001), 0.39± 0.25 (p< 0.0001), and 12 months 0.41± 0.23 (p< 0.0001) in the IRM group and 0.24± 0.16 (p< 0.0001), 0.27± 0.16 (p< 0.0001), 0.34± 0.17 (p< 0.0001), 0.38± 0.18 (p< 0.0001) in the BRM group. Baseline CMT was 420.39± 54.45 μm in IRM group and 407.82± 53.07 μm in BRM group. At 3, 6, 9, and 12 months, CMT decreased to 258.28± 20.4 μm (p< 0.0001), 268.38± 19.5 μm (p< 0.0001), 269.51± 32.41 μm (p< 0.0001), and 278.28± 16.56 μm (p< 0.0001) in the IRM group and 258.84± 17.47 μm (p< 0.0001), 265.69± 17.29 μm (p< 0.0001), 273.64± 23.13 μm (p< 0.0001), and 283.09± 19.66 μm (p< 0.0001) in the BRM group. Similar improvements in IRF and SRF levels in the patients were noted in both groups. Required number of doses of IRM and BRM was similar over the 12 month period in both groups. A similar profile of adverse events was noted in both the groups.Conclusion: Intravitreal injection of IRM and BRM show similar efficacy and safety in Indian eyes with nAMD.Keywords: neovascular age-related macular degeneration, anti-VEGF, ranibizumab, biosimilar ranibizumab
Published: 2023

42. Psychometric evaluation of the Indolent Systemic Mastocytosis Symptom Assessment Form (ISM-SAF©) and determination of a threshold score for moderate symptoms

Author: Alan L. Shields, Fiona Taylor, Roger E. Lamoureux, Brad Padilla, Kas Severson, Tanya Green, Anthony L. Boral, Cem Akin, Frank Siebenhaar, and Brenton Mar
Subjects: Psychometric evaluation, Instrument development, Patient-reported outcomes, Indolent systemic mastocytosis, Medicine
Abstract: Abstract Background The Indolent Systemic Mastocytosis Symptom Assessment Form (ISM-SAF) (©Blueprint Medicines Corporation), a 12-item daily diary that assesses 11 signs and symptoms of indolent systemic mastocytosis (ISM) and smoldering systemic mastocytosis (SSM), was psychometrically evaluated among patients with ISM. Additionally, thresholds of the ISM-SAF total symptom score (TSS) to distinguish patients with moderate to severe symptoms from those with mild symptoms were evaluated. Methods The ISM-SAF was completed daily as an electronic diary in a prospective, observational study utilizing an online survey of patients with ISM in the United States. Descriptive statistics, psychometric analyses, and analyses to estimate ISM-SAF TSS clinical cutoff values were conducted. Results A total of 103 patients (81.6% female; mean age = 50.2 [± 12.6]) with a self-reported diagnosis of ISM or SSM (58 of whom also had a medically documented diagnosis) contributed to the analyses. Psychometric analysis supported the trustworthiness of the biweekly TSS, which was reliable (α > 0.8, ICC > 0.9), construct-valid, and able to distinguish among clinically distinct groups as specified by the Patient Global Impression of Severity, 12-item Short-Form Health Survey, and Mastocytosis Quality of Life Questionnaire (p
Published: 2023
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43. Combined Internal Limiting Membrane Peeling and Subretinal Balanced Salt Solution Injection: A Novel Technique to Unfold Congenital Falciform Folds

Author: Boral, Subhendu K., Dan, Shouvick, and Mitra, Santanu
Published: 2023
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44. Real-world experience with ruxolitinib for steroid-refractory acute graft-versus-host disease: a single center experience

Author: Spałek, Adrianna, Wieczorkiewicz-Kabut, Agata, Koclęga, Anna, Woźniczka, Krzysztof, Węglarz, Patryk, Boral, Kinga, Kata, Dariusz, Zielińska, Patrycja, and Helbig, Grzegorz
Published: 2022
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45. 1203 Targeted in vivo generation of CAR T and NK cells utilizing an engineered lentiviral vector platform

Author: James I Andorko, Ronnie M Russell, Bruce C Schnepp, Ramesh Singh, Debasish Boral, and Philip R Johnson
Subjects: Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Published: 2023
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46. MEQA: Manifold embedding quality assessment via anisotropic scaling and Kolmogorov-Smirnov test

Author: Boral, Subhadip, Sarkar, Mainak, and Ghosh, Ashish
Published: 2023
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47. Measles virus and rinderpest virus divergence dated to the sixth century BCE

Author: Düx, Ariane, Lequime, Sebastian, Patrono, Livia Victoria, Vrancken, Bram, Boral, Sengül, Gogarten, Jan F, Hilbig, Antonia, Horst, David, Merkel, Kevin, Prepoint, Baptiste, Santibanez, Sabine, Schlotterbeck, Jasmin, Suchard, Marc A, Ulrich, Markus, Widulin, Navena, Mankertz, Annette, Leendertz, Fabian H, Harper, Kyle, Schnalke, Thomas, Lemey, Philippe, and Calvignac-Spencer, Sébastien
Subjects: Infection, Good Health and Well Being, Cities, Communicable Diseases, Emerging, Evolution, Molecular, Genetic Variation, History, Ancient, Humans, Measles, Measles virus, Rinderpest virus, General Science & Technology
Abstract: Many infectious diseases are thought to have emerged in humans after the Neolithic revolution. Although it is broadly accepted that this also applies to measles, the exact date of emergence for this disease is controversial. We sequenced the genome of a 1912 measles virus and used selection-aware molecular clock modeling to determine the divergence date of measles virus and rinderpest virus. This divergence date represents the earliest possible date for the establishment of measles in human populations. Our analyses show that the measles virus potentially arose as early as the sixth century BCE, possibly coinciding with the rise of large cities.
Published: 2020

48. Incidence, clinical features, risk factors, and outcomes of Intraocular inflammation following Brolucizumab in Indian eyes – A multicentric study

Author: Debdulal Chakraborty, Soumen Mondal, Sabyasachi Sengupta, Zahir Abbas, Khushboo Chandra, Subhendu Boral, Aniruddha Maiti, Sangeeta Roy, Angshuman Mukherjee, Arnab Das, Somnath Chakraborty, and Pinaki Nag
Subjects: aflibercept, brolucizumab, intraocular inflammation following brolucizumab, namd, Ophthalmology, RE1-994
Abstract: Purpose: To report the incidence, clinical features, potential risk factors, and outcomes of intraocular inflammation (IOI) following brolucizumab in Indian eyes. Methods: All consecutive patients diagnosed with brolucizumab-induced IOI from 10 centers in eastern India between October 2020 and April 2022 were included. Results: Of 758 injections given during the study period across centers, 13 IOI events (1.7%) were recorded attributable to brolucizumab. The IOI occurred after the first dose in two eyes (15%) (median 45 days after brolucizumab), second dose in six eyes (46%) (median = 8.5 days), and third dose (39%) in the remaining five eyes (median 7 days). Reinjections of brolucizumab were administered at a median interval of 6 weeks (interquartile range = 4–10 weeks) in the 11 eyes, where IOI occurred after the second or third dose. Eyes that experienced IOI after the third dose had received a significantly greater number of previous antivascular endothelial growth factor injections (median = 8) compared to those who developed it after the first or second dose (median = 4) (P = 0.001). Anterior chamber cells were seen in almost all eyes (n = 11, 85%), while peripheral retinal hemorrhages were seen in two eyes, and one eye showed branch artery occlusion. Two-thirds of patients (n = 8, 62%) recovered with a combination of topical and oral steroids, while remaining recovered with topical steroids alone. Irreversible visual loss was not seen in any eye, and median vision recovered to pre-IOI levels by 3 months' time point. Conclusion: Brolucizumab-induced IOI was relatively rare, occurring in 1.7% of eyes, was more common after the second or third injection, especially in those who required frequent reinjections every 6 weeks, and occurred earlier with increasing number of previous brolucizumab injections. Continued surveillance is necessary even after repeated doses of brolucizumab.
Published: 2023
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49. Real-world outcomes and complications of different surgical approaches for significant submacular haemorrhages

Author: Subhendu Kumar Boral, Deepak Agarwal, Arnab Das, Debdulal Chakraborty, and Santanu Mandal
Subjects: 180-degree retinectomy, autologous rpe-choroid patch graft transplantations, submacular hemorrhage, subretinal rt-plasminogen activator (pa), Ophthalmology, RE1-994
Abstract: Purpose: To evaluate the outcomes and complications after different surgical management of cases with significant sumacular hemorrhage (SMH) of size more than 4 disc diameter (DD). Methods: It was a retrospective interventional study. All consecutive 103 cases of significant SMHs were treated by vitrectomy and divided into three groups. In Group A (8 weeks, extending beyond macula, n = 10), SMH removal with autologous retinal pigment epithelium (RPE)-Choroid patch graft transplantations with SO tamponade were performed. Parameters evaluated were best corrected visual acuity (BCVA), Optos, optical computerized tomography, and ultrasonography as required. Results: Significant visual improvement was seen from mean preoperative to mean postoperative BCVA in Group A (P < 0.001), Group B (P < 0.001), and Group C (P < 0.001). Postoperative complications were recurrent SMH (4.84% vs 12.90% vs 10%), vitreous hemorrhage (6.45%, GroupA), hyphema (4.84% vs 12.90% vs 10%), hypotony (nil vs 3.23% vs 20%), macular hole formation (6.45%, Group A), epiretinal membrane (16.13%, Group B), and retinal detachment (3.23%, Group A and 10%, Group C). Conclusion: Surgical approaches for significant submacular hemorrhage are visually awarding, though certain specific complications may arise.
Published: 2023
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50. Brolucizumab in Neovascular Age-Related Macular Degeneration – Indian Real-World Experience: The BRAILLE Study – Fifty-Two-Week Outcomes

Author: Chakraborty D, Maiti A, Sheth JU, Mondal S, Boral S, Nandi K, Sinha TK, and Das A
Subjects: brolucizumab, inflammation, age related macular degeneration, Ophthalmology, RE1-994
Abstract: Debdulal Chakraborty,1 Aniruddha Maiti,2 Jay U Sheth,3 Soumen Mondal,1 Subhendu Boral,1 Krishnendu Nandi,4 Tushar Kanti Sinha,1 Arnab Das1 1Department of Vitreoretinal Services, Disha Eye Hospitals, Kolkata, West Bengal, India; 2Department of Vitreoretinal Services, Global Eye Hospitals Eye, Kolkata, West Bengal, India; 3Department of Vitreoretinal Services, Shantilal Shanghvi Eye Institute, Mumbai, Maharashtra, India; 4Department of Vitreoretinal Services, Netralayam Super Speciality Eye Care Centre, Kolkata, West Bengal, IndiaCorrespondence: Debdulal Chakraborty, Department of Vitreoretinal services, Disha Eye Hospitals, Kolkata, West Bengal, India, Tel +91 9433059923, Email devdc@rediffmail.comPurpose: To report the 52-week real-world efficacy and safety outcomes of brolucizumab therapy for neovascular age-related macular degeneration (nAMD) in Indian eyes.Patients and Methods: A retrospective, multicentre chart analysis of 82 eyes of 82 patients with nAMD (switch therapy: 65 eyes; treatment-naïve: 17 eyes) with 52-week follow-up data was performed. Pro-re-nata re-treatment was offered based on visual and tomographic criteria. Changes in best-corrected visual acuity (BCVA), intraretinal fluid (IRF), subretinal fluid (SRF), central-subfield thickness (CST), and pigment epithelial detachment (PED) were the key outcome measures, coupled with the safety profile.Results: The mean age of the study population was 67.65 (± 10.67) years, with 57 male patients (69.5%). The study’s mean number of injections was 4.8 (± 0.77). After brolucizumab therapy, the BCVA improved significantly at weeks 4 (P< 0.001), and maintained up to week 52 (P< 0.001). The CST also reduced significantly at all the visits (Baseline: 413.6 ± 64.6 μm; 52-week: 292.37 ± 13.5 μm; P< 0.001). Significantly fewer eyes demonstrated residual SRF (P< 0.001) and IRF (P< 0.001) at all visits, starting with week 12 and continuing until week 52. The PED resolution was significant from week 24 through week 52 (P=0.004). Each of the 82 eyes received four injections of brolucizumab, with 63.4% (52 eyes) receiving a fifth dose and only 17.1% requiring a sixth. Mild intraocular inflammation (IOI) was seen in three eyes (3.66%) that resolved conservatively. One patient (1.2%) developed mild fever that subsided with oral medications.Conclusion: The 52-week BRAILLE study demonstrates that brolucizumab is effective and safe in nAMD eyes in a real-world setting. Brolucizumab treatment can reduce the therapeutic burden in patients with nAMD due to its rapid, sustained efficacy and favourable safety profile.Keywords: brolucizumab, inflammation, age-related macular degeneration
Published: 2022

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