Zobrazeno 1 - 10
of 9 282
pro vyhledávání: '"Sterner A"'
We present a Python package called Modular Petri Net Assembly Toolkit (MPAT) that empowers users to easily create large-scale, modular Petri Nets for various spatial configurations, including extensive spatial grids or those derived from shape files,
Externí odkaz:
http://arxiv.org/abs/2407.10372
Petri nets are a promising modeling framework for epidemiology, including the spread of disease across populations or within an individual. In particular, the Susceptible-Infectious-Recovered (SIR) compartment model is foundational for population epi
Externí odkaz:
http://arxiv.org/abs/2407.10019
We explore graph rewiring methods that optimise commute time. Recent graph rewiring approaches facilitate long-range interactions in sparse graphs, making such rewirings commute-time-optimal on average. However, when an expert prior exists on which n
Externí odkaz:
http://arxiv.org/abs/2407.08762
Segmenting text into sentences plays an early and crucial role in many NLP systems. This is commonly achieved by using rule-based or statistical methods relying on lexical features such as punctuation. Although some recent works no longer exclusively
Externí odkaz:
http://arxiv.org/abs/2406.16678
Autor:
Schumm, Leon, Abdel-Khalek, Hazem, Brown, Tom, Ueckerdt, Falko, Sterner, Michael, Fioriti, Davide, Parzen, Max
As global demand for green hydrogen rises, potential hydrogen exporters move into the spotlight. However, the large-scale installation of on-grid hydrogen electrolysis for export can have profound impacts on domestic energy prices and energy-related
Externí odkaz:
http://arxiv.org/abs/2405.14717
Two approaches have emerged to input images into large language models (LLMs). The first is to caption images into natural language. The second is to map image feature embeddings into the domain of the LLM and pass the mapped embeddings directly to t
Externí odkaz:
http://arxiv.org/abs/2403.11317
Autor:
Buie, Marc W., Spencer, John R., Porter, Simon B., Benecchi, Susan D., Parker, Alex H., Stern, S. Alan, Belton, Michael, Binzel, Richard P., Borncamp, David, DeMeo, Francesca, Fabbro, S., Fuentes, Cesar, Furusawa, Hisanori, Fuse, Tetsuharu, Gay, Pamela L., Gwyn, Stephen, Holman, Matthew J., Karoji, H., Kavelaars, J. J., Kinoshita, Daisuke, Miyazaki, Satoshi, Mountain, Matt, Noll, Keith S., Osip, David J., Petit, Jean-Marc, Reid, Neill I., Sheppard, Scott S., Showalter, Mark, Steffl, Andrew J., Sterner, Ray E., Tajitsu, Akito, Tholen, David J., Trilling, David E., Weaver, Harold A., Verbiscer, Anne J., Wasserman, Lawrence H., Yamashita, Takuji, Yanagisawa, Toshifumi, Yoshida, Fumi, Zangari, Amanda M.
Following the Pluto fly-by of the New Horizons spacecraft, the mission provided a unique opportunity to explore the Kuiper Belt in-situ. The possibility existed to fly-by a Kuiper Belt object (KBO) as well as to observe additional objects at distance
Externí odkaz:
http://arxiv.org/abs/2403.04927
Autor:
Amaia Bacigalupe, Unai Martín, Federico Triolo, Linnea Sjöberg, Therese Rydberg Sterner, Serhiy Dekhtyar, Laura Fratiglioni, Amaia Calderón-Larrañaga
Publikováno v:
International Journal for Equity in Health, Vol 23, Iss 1, Pp 1-9 (2024)
Abstract Background As compared to men, older women´s higher rates of depression diagnosis and antidepressant use are widely reported. We aimed to: a) explore whether there is a potential gender bias in the clinical diagnosis of depression and antid
Externí odkaz:
https://doaj.org/article/26b49f15a6054bf3848096d075157bda
Autor:
Aimée Ekman, Sandra Pennbrant, Anders Sterner, Elenita Forsberg, Lena Hedén, Håkan Nunstedt, Annelie J. Sundler, Margaretha Larsson, Ingrid Larsson, Inger Ahlstrand, Hammar Isabelle Andersson, Qarin Lood, Jenny Hallgren
Publikováno v:
BMC Public Health, Vol 24, Iss 1, Pp 1-11 (2024)
Abstract Background It has been suggested that the university environment, to improve students’ health status and educational outcomes, should be based on a health promoting approach. More knowledge is needed about health promoting resources and li
Externí odkaz:
https://doaj.org/article/465a4bae8c16480c9ae08f57d2db771f
We describe a novel dataset for the automated recognition of named taxonomic and other entities relevant to the association of viruses with their hosts. We further describe some initial results using pre-trained models on the named-entity recognition
Externí odkaz:
http://arxiv.org/abs/2305.13317