Zobrazeno 1 - 10
of 7 654
pro vyhledávání: '"Paquin, P."'
Publikováno v:
J. Chem. Phys. 161, 034108 (2024) 1-8
Voltage distribution in sub-cellular micro-domains such as neuronal synapses, small protrusions or dendritic spines regulates the opening and closing of ionic channels, energy production and thus cellular homeostasis and excitability. Yet how voltage
Externí odkaz:
http://arxiv.org/abs/2407.15697
Autor:
Erika Chávez-Nungaray
Publikováno v:
Nóesis, Vol 28, Pp 116-119 (2019)
Externí odkaz:
https://doaj.org/article/4d882cd4a28b44de8a5ef4be4641c107
Autor:
Omidi, Amir, Banawan, Mai, Weckenmann, Erwan, Paquin, Benoit, Geravand, Alireza, Zheng, Zibo, Shi, Wei, Zeng, Ming, Rusch, Leslie A.
We examine pulse amplitude modulation (PAM) for intensity modulation and direct detection systems. Using a straight-forward, mixed noise model, we optimize the constellations with an autoencoder-based neural network (NN), an improve required signal-t
Externí odkaz:
http://arxiv.org/abs/2402.04395
Autor:
South, Tobin, Camuto, Alexander, Jain, Shrey, Nguyen, Shayla, Mahari, Robert, Paquin, Christian, Morton, Jason, Pentland, Alex 'Sandy'
In a world of increasing closed-source commercial machine learning models, model evaluations from developers must be taken at face value. These benchmark results-whether over task accuracy, bias evaluations, or safety checks-are traditionally impossi
Externí odkaz:
http://arxiv.org/abs/2402.02675
Autor:
Blanco-Cuaresma, Sergi, Ciucă, Ioana, Accomazzi, Alberto, Kurtz, Michael J., Henneken, Edwin A., Lockhart, Kelly E., Grezes, Felix, Allen, Thomas, Shapurian, Golnaz, Grant, Carolyn S., Thompson, Donna M., Hostetler, Timothy W., Templeton, Matthew R., Chen, Shinyi, Koch, Jennifer, Jacovich, Taylor, Chivvis, Daniel, Alves, Fernanda de Macedo, Paquin, Jean-Claude, Bartlett, Jennifer, Polimera, Mugdha, Jarmak, Stephanie
Open-source Large Language Models enable projects such as NASA SciX (i.e., NASA ADS) to think out of the box and try alternative approaches for information retrieval and data augmentation, while respecting data copyright and users' privacy. However,
Externí odkaz:
http://arxiv.org/abs/2312.14211
The flow of ions through permeable channels causes voltage drop in physiological nanodomains such as synapses, dendrites and dendritic spines, and other protrusions. How the voltage changes around channels in these nanodomains has remained poorly stu
Externí odkaz:
http://arxiv.org/abs/2311.08169
Akademický článek
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Autor:
Mohammad Arif Rahman, Massimiliano Bissa, Hanna Scinto, Savannah E. Howe, Sarkis Sarkis, Zhong-Min Ma, Anna Gutowska, Xunqing Jiang, Christina C. Luo, Luca Schifanella, Ramona Moles, Isabela Silva de Castro, Shraddha Basu, Kombo F. N’guessan, LaTonya D. Williams, Manuel Becerra-Flores, Melvin N. Doster, Tanya Hoang, Hyoyoung Choo-Wosoba, Emmanuel Woode, Yongjun Sui, Georgia D. Tomaras, Dominic Paquin-Proulx, Mangala Rao, James D. Talton, Xiang-Peng Kong, Susan Zolla-Pazner, Timothy Cardozo, Genoveffa Franchini, Jay A. Berzofsky
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-19 (2024)
Abstract Systemic vaccination of macaques with V1-deleted (ΔV1) envelope immunogens reduce the risk of SIVmac251 acquisition by approximately 60%, with protective roles played by V2-specific ADCC and envelope-specific mucosal IL-17+NKp44+ innate lym
Externí odkaz:
https://doaj.org/article/c46022c8eff943a69e28ba2d4818429f
Publikováno v:
BMC Health Services Research, Vol 24, Iss 1, Pp 1-13 (2024)
Abstract Background Recently, our research team developed an open source and free website called the MEPP website (for the Mirror Effect Plus Protocol) to efficiently provide mirror therapy for patients with facial palsy. Previous studies demonstrate
Externí odkaz:
https://doaj.org/article/24c0c695af984c0c9289427d4bcf5587
Autor:
Beeler, Chris, Subramanian, Sriram Ganapathi, Sprague, Kyle, Chatti, Nouha, Bellinger, Colin, Shahen, Mitchell, Paquin, Nicholas, Baula, Mark, Dawit, Amanuel, Yang, Zihan, Li, Xinkai, Crowley, Mark, Tamblyn, Isaac
This paper provides a simulated laboratory for making use of Reinforcement Learning (RL) for chemical discovery. Since RL is fairly data intensive, training agents `on-the-fly' by taking actions in the real world is infeasible and possibly dangerous.
Externí odkaz:
http://arxiv.org/abs/2305.14177