Zobrazeno 1 - 10
of 8 630
pro vyhledávání: '"J, McDonald"'
Autor:
J. Liebmann, B. Ware, D. R. Mole, C. L. Kirkland, G. Fraser, K. Waltenberg, S. Bodorkos, D. L. Huston, N. J. Evans, B. J. McDonald, K. Rankenburg, P. Datta, S. Tessalina
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-11 (2024)
Abstract Lead isotopes are a powerful geochemical tracer and a popular tool applied across a broad range of scientific fields, e.g., earth sciences, archaeology, and forensic sciences. Here we present a Pb isotope dataset collected from 232 igneous s
Externí odkaz:
https://doaj.org/article/dd41b055b84c4ab5b7a30754d2145b00
Autor:
Leanne S. Fawkes, Taehyun Roh, Thomas J. McDonald, Jennifer A. Horney, Weihsueh A. Chiu, Garett T. Sansom
Publikováno v:
Archives of Public Health, Vol 82, Iss 1, Pp 1-8 (2024)
Abstract The Greater Fifth Ward (GFW) is a Northeast Houston, Texas, neighborhood with a legacy of industrial contamination and a confirmed cancer cluster. To understand self-rated health in the GFW, community-based participatory research (CBPR), was
Externí odkaz:
https://doaj.org/article/5820a5c0c7a449f3bf943577096d1266
Publikováno v:
Vertebrate Zoology, Vol 74, Iss , Pp 577-594 (2024)
Abstract Stable upland habitats in arid zone biomes are often characterised by locally endemic lineages. Explanations for this pattern include habitat or substrate specialisation (ecological specialisation) or intensifying aridity driving retreat int
Externí odkaz:
https://doaj.org/article/94a5a25086224bd097c24e23b89c688f
Publikováno v:
Atmospheric Measurement Techniques, Vol 17, Pp 5765-5784 (2024)
The use of depolarization lidar to measure atmospheric volume depolarization ratio (VDR) is a common technique to classify cloud phase (liquid or ice). Previous work using a machine learning framework, applied to peak properties derived from co-polar
Externí odkaz:
https://doaj.org/article/ad304abe7f534845a6a9e19e94d28853
Autor:
Hari Sankar Nayak, Andrew J. McDonald, Virender Kumar, Peter Craufurd, Shantanu Kumar Dubey, Amaresh Kumar Nayak, Chiter Mal Parihar, Panneerselvam Peramaiyan, Shishpal Poonia, Kindie Tesfaye, Ram K. Malik, Anton Urfels, Udham Singh Gautam, João Vasco Silva
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-11 (2024)
Abstract Yield gap analysis is used to characterize the untapped production potential of cropping systems. With emerging large-n agronomic datasets and data science methods, pathways for narrowing yield gaps can be identified that provide actionable
Externí odkaz:
https://doaj.org/article/eb110cbc8d3a428da5f4a0551c7d5755
Autor:
Zia Uddin Ahmed, Timothy J. Krupnik, Jagadish Timsina, Saiful Islam, Khaled Hossain, A.S.M. Alanuzzaman Kurishi, Shah-Al Emran, M. Harun-Ar-Rashid, Andrew J. McDonald, Mahesh K. Gathala
Publikováno v:
Artificial Intelligence in Agriculture, Vol 13, Iss , Pp 100-116 (2024)
Knowledge of the factors influencing nutrient-limited subtropical maize yield and subsequent prediction is crucial for effective nutrient management, maximizing profitability, ensuring food security, and promoting environmental sustainability. We ana
Externí odkaz:
https://doaj.org/article/fa7b347940614a568aadba9707ee4851
Autor:
Anna Maria Moran, Vi T. Vo, Kevin J. McDonald, Pranav Sultania, Eva Langenbrunner, Jun Hong Vince Chong, Amartya Naik, Lorenzo Kinnicutt, Jingshuo Li, Tommaso Ranzani
Publikováno v:
Communications Engineering, Vol 3, Iss 1, Pp 1-13 (2024)
Abstract To achieve coordinated functions, fluidic soft robots typically rely on multiple input lines for the independent inflation and deflation of each actuator. Fluidic actuators are controlled by rigid electronic pneumatic valves, restricting the
Externí odkaz:
https://doaj.org/article/79a4378103b84cc4a009b52b5875848c
Autor:
Sarabeth M. Mathis, Alexander E. Webber, Tomás M. León, Erin L. Murray, Monica Sun, Lauren A. White, Logan C. Brooks, Alden Green, Addison J. Hu, Roni Rosenfeld, Dmitry Shemetov, Ryan J. Tibshirani, Daniel J. McDonald, Sasikiran Kandula, Sen Pei, Rami Yaari, Teresa K. Yamana, Jeffrey Shaman, Pulak Agarwal, Srikar Balusu, Gautham Gururajan, Harshavardhan Kamarthi, B. Aditya Prakash, Rishi Raman, Zhiyuan Zhao, Alexander Rodríguez, Akilan Meiyappan, Shalina Omar, Prasith Baccam, Heidi L. Gurung, Brad T. Suchoski, Steve A. Stage, Marco Ajelli, Allisandra G. Kummer, Maria Litvinova, Paulo C. Ventura, Spencer Wadsworth, Jarad Niemi, Erica Carcelen, Alison L. Hill, Sara L. Loo, Clifton D. McKee, Koji Sato, Claire Smith, Shaun Truelove, Sung-mok Jung, Joseph C. Lemaitre, Justin Lessler, Thomas McAndrew, Wenxuan Ye, Nikos Bosse, William S. Hlavacek, Yen Ting Lin, Abhishek Mallela, Graham C. Gibson, Ye Chen, Shelby M. Lamm, Jaechoul Lee, Richard G. Posner, Amanda C. Perofsky, Cécile Viboud, Leonardo Clemente, Fred Lu, Austin G. Meyer, Mauricio Santillana, Matteo Chinazzi, Jessica T. Davis, Kunpeng Mu, Ana Pastore y Piontti, Alessandro Vespignani, Xinyue Xiong, Michal Ben-Nun, Pete Riley, James Turtle, Chis Hulme-Lowe, Shakeel Jessa, V. P. Nagraj, Stephen D. Turner, Desiree Williams, Avranil Basu, John M. Drake, Spencer J. Fox, Ehsan Suez, Monica G. Cojocaru, Edward W. Thommes, Estee Y. Cramer, Aaron Gerding, Ariane Stark, Evan L. Ray, Nicholas G. Reich, Li Shandross, Nutcha Wattanachit, Yijin Wang, Martha W. Zorn, Majd Al Aawar, Ajitesh Srivastava, Lauren A. Meyers, Aniruddha Adiga, Benjamin Hurt, Gursharn Kaur, Bryan L. Lewis, Madhav Marathe, Srinivasan Venkatramanan, Patrick Butler, Andrew Farabow, Naren Ramakrishnan, Nikhil Muralidhar, Carrie Reed, Matthew Biggerstaff, Rebecca K. Borchering
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-13 (2024)
Abstract Accurate forecasts can enable more effective public health responses during seasonal influenza epidemics. For the 2021–22 and 2022–23 influenza seasons, 26 forecasting teams provided national and jurisdiction-specific probabilistic predi
Externí odkaz:
https://doaj.org/article/b22341a399b644b886f816887477dc5b
Publikováno v:
Frontiers in Computational Neuroscience, Vol 18 (2024)
Deep Reinforcement Learning is a branch of artificial intelligence that uses artificial neural networks to model reward-based learning as it occurs in biological agents. Here we modify a Deep Reinforcement Learning approach by imposing a suppressive
Externí odkaz:
https://doaj.org/article/f2d9fc242ff44e6bad07aec30229b85b
Publikováno v:
Communications Biology, Vol 7, Iss 1, Pp 1-11 (2024)
Abstract Human learning varies greatly among individuals and is related to the microstructure of major white matter tracts in several learning domains, yet the impact of the existing microstructure of white matter tracts on future learning outcomes r
Externí odkaz:
https://doaj.org/article/310c6f799d6b4d9d94a1cc15f96e0e81