Zobrazeno 1 - 10
of 8 306
pro vyhledávání: '"Ming C"'
Autor:
Abhilash Prabhat, Dema Sami, Allison Ehlman, Isabel Stumpf, Tanya Seward, Wen Su, Ming C. Gong, Elizabeth A. Schroder, Brian P. Delisle
Publikováno v:
Communications Biology, Vol 7, Iss 1, Pp 1-14 (2024)
Abstract Shift work and artificial light at night disrupt the entrainment of endogenous circadian rhythms in physiology and behavior to the day-night cycle. We hypothesized that exposure to dim light at night (dLAN) disrupts feeding rhythms, leading
Externí odkaz:
https://doaj.org/article/12fddcbea3314db0b52075aa34aa9390
Autor:
Vafi Salmasi, Mohammad Reza Rasouli, Ming C. Kao, Einar Ottestad, Abdullah Sulieman Terkawi, Garret Morris, Xiang Qian, Stephen Coleman, David C. Talavera, Heather Poupore-King, Kristen Slater, Michael S. Leong
Publikováno v:
Frontiers in Pain Research, Vol 4 (2024)
IntroductionPsychological evaluation is required by insurance companies in the United States prior to proceeding with a spinal cord stimulation or a dorsal root ganglion stimulation trial. Since January 2017, we implemented a Multidisciplinary Team C
Externí odkaz:
https://doaj.org/article/97de90e270bb485ca4c34ead7a90fe1e
Autor:
Bala S C Koritala, Yin Yeng Lee, Laetitia S Gaspar, Shweta S Bhadri, Wen Su, Gang Wu, Lauren J Francey, Marc D Ruben, Ming C Gong, John B Hogenesch, David F Smith
Publikováno v:
PLoS Biology, Vol 21, Iss 5, p e3002139 (2023)
Intermittent hypoxia (IH) is a major clinical feature of obstructive sleep apnea (OSA). The mechanisms that become dysregulated after periods of exposure to IH are unclear, particularly in the early stages of disease. The circadian clock governs a wi
Externí odkaz:
https://doaj.org/article/e04c4b5965044dc0abdef46011780cda
Autor:
Jacobson, Philip, Xie, Yichen, Ding, Mingyu, Xu, Chenfeng, Tomizuka, Masayoshi, Zhan, Wei, Wu, Ming C.
Semi-supervised 3D object detection is a common strategy employed to circumvent the challenge of manually labeling large-scale autonomous driving perception datasets. Pseudo-labeling approaches to semi-supervised learning adopt a teacher-student fram
Externí odkaz:
http://arxiv.org/abs/2409.10901
3D-free meets 3D priors: Novel View Synthesis from a Single Image with Pretrained Diffusion Guidance
Recent 3D novel view synthesis (NVS) methods are limited to single-object-centric scenes and struggle with complex environments. They often require extensive 3D data for training, lacking generalization beyond the training distribution. Conversely, 3
Externí odkaz:
http://arxiv.org/abs/2408.06157
Publikováno v:
Frontiers in Nutrition, Vol 9 (2022)
Disruption of blood pressure (BP) circadian rhythm, independent of hypertension, is emerging as an index for future target organ damage and is associated with a higher risk of cardiovascular events. Previous studies showed that changing food availabi
Externí odkaz:
https://doaj.org/article/f90875bd9dc04882b46d691bea0665be
Publikováno v:
Computational Visual Media, Vol 9, Iss 3, Pp 405-405 (2023)
Externí odkaz:
https://doaj.org/article/78658b0645ec479f815b0d6df7e6d7ce
Autor:
Rebecca C Lowry, Zachary F Hallberg, Rob Till, Tyler J Simons, Ruth Nottingham, Fiona Want, R Elizabeth Sockett, Ming C Hammond, Carey Lambert
Publikováno v:
PLoS Genetics, Vol 18, Iss 5, p e1010164 (2022)
Bacterial second messengers are important for regulating diverse bacterial lifestyles. Cyclic di-GMP (c-di-GMP) is produced by diguanylate cyclase enzymes, named GGDEF proteins, which are widespread across bacteria. Recently, hybrid promiscuous (Hypr
Externí odkaz:
https://doaj.org/article/0547c364590f4a9aa39c405a5d63c08f
Autor:
Thalapanane, Sandeep, Kumar, Sandip Sharan Senthil, Peethambari, Guru Nandhan Appiya Dilipkumar, SriHari, Sourang, Zheng, Laura, Poveda, Julio, Lin, Ming C.
Data for training learning-enabled self-driving cars in the physical world are typically collected in a safe, normal environment. Such data distribution often engenders a strong bias towards safe driving, making self-driving cars unprepared when enco
Externí odkaz:
http://arxiv.org/abs/2407.09466
Vector fields are widely used to represent and model flows for many science and engineering applications. This paper introduces a novel neural network architecture for learning tangent vector fields that are intrinsically defined on manifold surfaces
Externí odkaz:
http://arxiv.org/abs/2406.09648