Tootfinder

#LB Mais um boost pois todo mundo precisa conhecer este resultado super relevante da ciência rs.
https://social.linux.pizza/@matematico314/114747559707121310

A bibliometric study on mathematical oncology: interdisciplinarity, internationality, collaboration and trending topics
Kira Pugh, Linn\'ea Gyllingberg, Stanislav Stratiev, Sara Hamis
https://arxiv.org/abs/2506.20684

A bibliometric study on mathematical oncology: interdisciplinarity, internationality, collaboration and trending topics
Mathematical oncology is an interdisciplinary research field where mathematics meets cancer research. The field's intention to study cancer makes it dynamic, as practicing researchers are incentivised to quickly adapt to both technical and medical research advances. Determining the scope of mathematical oncology is therefore not straightforward; however, it is important for purposes related to funding allocation, education, scientific communication, and community organisation. To address this i…

Mathematical Modelling and Optimisation of Athletic Performance: Tapering and Periodisation
David Ceddia, Howard Bondell, Peter Taylor
https://arxiv.org/abs/2505.20859

Mathematical Modelling and Optimisation of Athletic Performance: Tapering and Periodisation
We conduct a mathematical optimisation of the training load to maximise performance for two seminal athletic performance models: the Banister et al. 1975 Fitness-Fatigue Impulse Response Model and the Busso 2003 Variable Dose-Response Model. We discuss discrepancies in the general trends of the optimised training loads compared to common training practices recommended in the sports science literature, such as tapering and periodisation. We then propose a set of interpretable nonlinear modificat…

Mathematics may be defined as the subject in which we never know what we are talking about, nor whether what we are saying is true.
—Bertrand Russell

An object-centric core metamodel for IoT-enhanced event logs
Yannis Bertrand, Christian Imenkamp, Lukas Malburg, Matthias Ehrendorfer, Marco Franceschetti, Joscha Gr\"uger, Francesco Leotta, J\"urgen Mangler, Ronny Seiger, Agnes Koschmider, Stefanie Rinderle-Ma, Barbara Weber, Estefania Serral
https://arxiv.org/abs/250…

An object-centric core metamodel for IoT-enhanced event logs
Advances in Internet-of-Things (IoT) technologies have prompted the integration of IoT devices with business processes (BPs) in many organizations across various sectors, such as manufacturing, healthcare and smart spaces. The proliferation of IoT devices leads to the generation of large amounts of IoT data providing a window on the physical context of BPs, which facilitates the discovery of new insights about BPs using process mining (PM) techniques. However, to achieve these benefits, IoT dat…

Diophantine Equations over $\mathbb Z$: Universal Bounds and Parallel Formalization
Jonas Bayer, Marco David, Malte Hassler, Yuri Matiyasevich, Dierk Schleicher
https://arxiv.org/abs/2506.20909

Diophantine Equations over $\mathbb Z$: Universal Bounds and Parallel Formalization
This paper explores multiple closely related themes: bounding the complexity of Diophantine equations over the integers and developing mathematical proofs in parallel with formal theorem provers. Hilbert's Tenth Problem (H10) asks about the decidability of Diophantine equations and has been answered negatively by Davis, Putnam, Robinson and Matiyasevich. It is natural to ask for which subclasses of Diophantine equations H10 remains undecidable. Such subclasses can be defined in terms of unive…

#LB Boost no meu próprio post pois mais gente merece conhecer esta pesquisa científica de extrema relevância! rs
https://social.linux.pizza/@matematico314/11474755970712131…

Hybrid Machine Learning and Mathematical Modeling for Tumor Dynamics Prediction: Comparing SPIONs against mNP-FDG
Amit K Chattopadhyay, Aimee Pascaline N Unkundiye, Gillian Pearce
https://arxiv.org/abs/2505.21094

Hybrid Machine Learning and Mathematical Modeling for Tumor Dynamics Prediction: Comparing SPIONs against mNP-FDG
This is a Machine Learning guided study towards zone-specific ray therapy. Combining Machine Learning (Extreme Gradient Boosting) with continuum modeling (exponential and logistic growth), we find that while fluorodeoxyglucose-coated (mNP-FDG) can control cancerous tumor progression within 2 days compared to 18 days by Superparamagnetic Iron Oxide Nanoparticles (SPIONs), for complete termination of the tumor, SPIONS (20 days) are superior compared to mNP-FDG (more than 40 days). We also provide…

Sono do caramba, mas eu preciso largar isso daqui e trabalhar. 😩

Encontrei na geladeira uma lata de coca-cola que venceu em fevereiro. Eu bebi assim mesmo, pois eu me recuso a acreditar que coca-cola estraga rs.