Results 1 to 10 of about 2,658 (164)

Event generation with Sherpa 2.2 [PDF]

SciPost Physics, 2019
Sherpa is a general-purpose Monte Carlo event generator for the simulation of particle collisions in high-energy collider experiments. We summarize essential features and improvements of the Sherpa 2.2 release series, which is heavily used for event ...
Enrico Bothmann, Gurpreet Singh Chahal, Stefan Höche, Johannes Krause, Frank Krauss, Silvan Kuttimalai, Sebastian Liebschner, Davide Napoletano, Marek Schönherr, Holger Schulz, Steffen Schumann, Frank Siegert
doaj   +7 more sources

Hard diffraction in SHERPA

European Physical Journal C: Particles and Fields
We present the first complete simulation framework for the simulation of jet production in diffractive events at next-to leading order in QCD, matched to the parton shower.
Frank Krauss, Peter Meinzinger
doaj   +3 more sources

Safety, effectiveness and immunogenicity of heterologous mRNA-1273 boost after prime with Ad26.COV2.S among healthcare workers in South Africa: The single-arm, open-label, phase 3 SHERPA study. [PDF]

PLOS Global Public Health
Limited studies have been conducted on the safety and effectiveness of heterologous COVID-19 vaccine boosting in lower income settings, especially those with high-HIV prevalence., The Sisonke Heterologous mRNA-1273 boost after prime with Ad26.COV2.S ...
Nigel Garrett, Tarylee Reddy, Nonhlanhla Yende-Zuma, Azwidhwi Takalani, Kubashni Woeber, Annie Bodenstein, Phumeza Jonas, Imke Engelbrecht, Waasila Jassat, Harry Moultrie, Debbie Bradshaw, Ishen Seocharan, Jackline Odhiambo, Kentse Khuto, Simone I Richardson, Millicent A Omondi, Rofhiwa Nesamari, Roanne S Keeton, Catherine Riou, Thandeka Moyo-Gwete, Craig Innes, Zwelethu Zwane, Kathy Mngadi, William Brumskine, Nivashnee Naicker, Disebo Potloane, Sharlaa Badal-Faesen, Steve Innes, Shaun Barnabas, Johan Lombaard, Katherine Gill, Maphoshane Nchabeleng, Elizma Snyman, Friedrich Petrick, Elizabeth Spooner, Logashvari Naidoo, Dishiki Kalonji, Vimla Naicker, Nishanta Singh, Rebone Maboa, Pamela Mda, Daniel Malan, Anusha Nana, Mookho Malahleha, Philip Kotze, Jon J Allagappen, Andreas H Diacon, Gertruida M Kruger, Faeezah Patel, Penny L Moore, Wendy A Burgers, Kate Anteyi, Brett Leav, Linda-Gail Bekker, Glenda E Gray, Ameena Goga, SHERPA study team   +56 more
doaj   +2 more sources

The blunted vascular endothelial growth factor-A (VEGF-A) response to high-altitude hypoxia and genetic variants in the promoter region of the VEGFA gene in Sherpa highlanders [PDF]

PeerJ, 2022
Background Sherpa highlanders demonstrate extraordinary tolerance to hypoxia at high altitudes, which may be achieved by mechanisms promoting microcirculatory blood flow and capillary density at high altitudes for restoring oxygen supply to tissues ...
Yunden Droma, Masayuki Hanaoka, Takumi Kinjo, Nobumitsu Kobayashi, Masanori Yasuo, Yoshiaki Kitaguchi, Masao Ota   +6 more
doaj   +2 more sources

Usefulness of Automatic Hyperparameter Optimization in Developing Radiation Emulator in a Numerical Weather Prediction Model

Atmosphere, 2022
To improve the forecasting accuracy of a radiation emulator in a weather prediction model over the Korean peninsula, the learning rate used in neural network training was automatically optimized using the Sherpa.
Park Sa Kim, Hwan-Jin Song
doaj   +1 more source

Pulmonary vascular reactivity to supplemental oxygen in Sherpa and lowlanders during gradual ascent to high altitude

Experimental Physiology, 2023
Prolonged alveolar hypoxia leads to pulmonary vascular remodelling. We examined the time course at altitude, over which hypoxic pulmonary vasoconstriction goes from being acutely reversible to potentially irreversible. Study subjects were lowlanders (n = 
Prajan Subedi, Christopher Gasho, Michael Stembridge, Alexandra M. Williams, Alexander Patrician, Philip N. Ainslie, James D. Anholm   +6 more
doaj   +1 more source

Sherpa: Robust hyperparameter optimization for machine learning

SoftwareX, 2020
Sherpa is a hyperparameter optimization library for machine learning models. It is specifically designed for problems with computationally expensive, iterative function evaluations, such as the hyperparameter tuning of deep neural networks.
Lars Hertel, Julian Collado, Peter Sadowski, Jordan Ott, Pierre Baldi   +4 more
doaj   +1 more source

The Potential Impact of Digital Biomarkers in Multiple Sclerosis in The Netherlands: An Early Health Technology Assessment of MS Sherpa

Brain Sciences, 2021
(1) Background: Monitoring of Multiple Sclerosis (MS) with eHealth interventions or digital biomarkers provides added value to the current care path. Evidence in the literature is currently scarce.
Sonja Cloosterman, Inez Wijnands, Simone Huygens, Valérie Wester, Ka-Hoo Lam, Eva Strijbis, Bram den Teuling, Matthijs Versteegh   +7 more
doaj   +1 more source

Detecting strawberry diseases and pest infections in the very early stage with an ensemble deep-learning model

Frontiers in Plant Science, 2022
Detecting early signs of plant diseases and pests is important to preclude their progress and minimize the damages caused by them. Many methods are developed to catch signs of diseases and pests from plant images with deep learning techniques, however ...
Sangyeon Lee, Amarpreet Singh Arora, Choa Mun Yun   +2 more
doaj   +1 more source

Collection calendar: the diversity and local knowledge of wild edible plants used by Chenthang Sherpa people to treat seasonal food shortages in Tibet, China

Journal of Ethnobiology and Ethnomedicine, 2021
Background Wild edible plants (WEPs) are non-cultivated and non-domesticated plants used for food. WEPs provided food, nutrition, herbs and other plant products for people in underdeveloped areas, such as the Everest region, to maintain their daily lives.
Xiao-Yong Ding, Yu Zhang, Lu Wang, Hui-Fu Zhuang, Wen-Yun Chen, Yu-Hua Wang   +5 more
doaj   +1 more source